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Record W4399057010 · doi:10.1016/j.jsse.2024.05.003

Serendipitous detection of orbital debris by the International Liquid Mirror Telescope

2024· article· en· W4399057010 on OpenAlexafffund
Paul Hickson, Bhavya Ailawadhi, S. Arun, Monalisa Dubey, Naveen Dukiya, Sara Filali, Brajesh Kumar, Kuntal Misra, Vibhore Negi, Kumar Pranshu, Jean Surdej, Saakshi Turakhia

Bibliographic record

VenueJournal of Space Safety Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicSpace Satellite Systems and Control
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaFonds De La Recherche Scientifique - FNRSDepartment of Science and Technology, Ministry of Science and Technology, IndiaYork UniversityUniversité de LiègeEuropean Space Agency
KeywordsSpace debrisTelescopeDebrisRemote sensingAstronomyOpticsAerospace engineeringGeologyPhysicsEngineeringMeteorology

Abstract

fetched live from OpenAlex

The International Liquid Mirror Telescope is a 4-m zenith-pointing optical telescope that employs a rotating liquid primary mirror. Located in the Indian Himalayas, it began operations in October 2022. The telescope is equipped with a CCD camera that has a 22 x 22 arcmin field of view and employs time-delay integration readout to compensate for the Earth’s rotation. While its primary purpose is to conduct astronomical survey observations using broad-band filters, the telescope is also sensitive to objects in Earth orbit that pass through its field of view, leaving detectable streaks. We have examined all images obtained during the first year of observations and determined the transit times and position angles of all detected objects. These were compared with publicly available two-line elements, propagated to the time of observation, in order to identify cataloged objects. A total of 301 streaks were found in 1838 images. Of these, 64% were identified with cataloged objects. Most of the identified objects are in low-Earth orbit, in the altitude range of 400–1600 km. The apparent magnitudes of the identified objects range from 3.6 to 15.1 in the V band. It was also possible to infer angular rates, apparent magnitudes and altitudes for 29% of the unidentified objects. The V-band magnitudes range from 6.4 to 19.5 and the estimated altitudes range from 285 to over 300,000 km.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.479

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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes2
Has abstractyes

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