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Record W4414027523 · doi:10.3847/psj/adf8ca

The Visibility of the Ōtautahi–Oxford Interstellar Object Population Model in LSST

2025· article· en· W4414027523 on OpenAlex
Rosemary C. Dorsey, Matthew J. Hopkins, Michele T. Bannister, Samantha Lawler, Chris Lintott, A. H. Parker, John C. Forbes

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Planetary Science Journal · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsCampion CollegeUniversity of Regina
FundersAcademy of FinlandRoyal Society Te Apārangi
KeywordsVisibilityObject (grammar)PopulationComputer sciencePhysicsAstrobiologyMeteorologyArtificial intelligenceSociologyDemography

Abstract

fetched live from OpenAlex

Abstract With a new probabilistic technique for sampling interstellar object (ISO) orbits with high efficiency, we assess the observability of ISOs under a realistic cadence for the upcoming Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST). Using the Ōtautahi–Oxford population model, we show that there will be complex on-sky structure in the pattern of direction and velocity revealed by the detected ISO population, with the expected enhanced northern flux complicating efforts to derive population parameters from the LSST’s predominately southern footprint. For reasonable luminosity functions with slopes of 2.5 ≤ q s ≤ 4.0, the most discoverable ISOs have H r ≃ 14.6−20.7. The slope of the luminosity function of ISOs will be relatively quickly constrained by the characteristics of the LSST detected population, such as the distributions of perihelia, velocity at infinity, and discovery circumstances. Discoveries are evenly split around their perihelion passage and are biased to lower velocities. After their discovery by LSST, it will be rare for ISOs to be visible for less than a month; most will have m r ≤ 23 for months, and the window for spectroscopic characterization could be as long as 2 yr. While these probabilistic assessments are robust against model or spatial density refinements that change the absolute numbers of ISO discoveries, our simulations predict a yield of 6–51 asteroidal ISOs, which is similar to previous works and demonstrates the validity of our new methods.

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.

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)0.002
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 score0.133
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.232
Teacher spread0.225 · 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