MétaCan
Menu
Back to cohort
Record W7084395190 · doi:10.48577/jpl.klu0fu

Discovery and Preliminary Characterization of a Third Interstellar Object

2025· dataset· en· W7084395190 on OpenAlexaboutno aff

Bibliographic record

VenueJPL Data · 2025
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsnot available
Fundersnot available
KeywordsSolar SystemObservableUnobservableTelescopeEccentricity (behavior)Mars Exploration ProgramOrbital mechanicsObject (grammar)Solar telescope

Abstract

fetched live from OpenAlex

We report initial observations aimed at the characterization of a third interstellar object. This object, 3I/ATLAS or C/2025 N1 (ATLAS), was discovered on 2025 July 1 UT and has an orbital eccentricity of e ⇠ 6.1, perihelion of q ⇠ 1.36 au, inclination of ⇠ 175 , and hyperbolic velocity of V1 ⇠ 58 km s1 . We report deep stacked images obtained using the Canada-France-Hawaii Telescope and the Very Large Telescope that resolve a compact coma. Using images obtained from several smaller ground-based telescopes, we find minimal light curve variation for the object over a ⇠ 4 day time span. The visible/near-infrared spectral slope of the object is 17.1±0.2 %/100 nm, comparable to other interstellar objects and primitive solar system small bodies (comets and D-type asteroids). 3I/ATLAS will be observable through early September 2025, then unobservable by Earth-based observatories near perihelion due to low solar elongation. It will be observable again from the ground in late November 2025. Although this limitation unfortunately prohibits detailed Earth-based observations at perihelion when the activity of 3I/ATLAS is likely to peak, spacecraft at Mars could be used to make valuable observations at this time.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.006

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 head0.047
GPT teacher head0.319
Teacher spread0.272 · 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 designNot applicable
Domainnot available
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJPL DataSame topicListeria monocytogenes in Food SafetyFrench-language works237,207