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Record W2779282010 · doi:10.22323/1.301.0754

TAIGA-HiSCORE detection of the CATS-Lidar on the ISS as fast moving point source

2017· article· en· W2779282010 on OpenAlexfundno aff
R. Wischnewski, А. Порелли, A. Garmash, И. И. Астапов, P. A. Bezyazeekov, V. Boreyko, А. Бородин, Martin Brueckner, Н. Буднев, A. Chiavassa, A. N. Dyachok, Oleg Fedorov, A. Gafarov, N. Gorbunov, E. Gorbovskoy, V. Grebenyuk, О. Гресс, Т. И. Гресс, О. Гришин, A. A. Grinyuk, D. Horns, Ivanova La, Н. Н. Калмыков, Y. Kazarina, В. В. Киндин, Pavel Kirilenko, S. Kiryuhin, Р. П. Кокоулин, К. Г. Компаниец, Е. Е. Коростелева, Vladimir V Kozhin, Е. А. Кравченко, М. Куннас, L. A. Kuzmichev, Yu. Lemeshev, Vladimir Lenok, Б. Лубсандоржиев, V. Lipunov, Н. Лубсандоржиев, R. Mirgazov, Razmik Mirzoyan, Р. Монхоев, R. Nachtigall, E. Osipova, А. Пахоруков, M. I. Panasyuk, L. Pankov, А. А. Петрухин, V. Poleschuk, E. Popescu, Elena Popova, Е. Постников, В. В. Просин, В. С. Птускин, E.V. Rjabov, Г. И. Рубцов, А. Пушнин, Yaroslav Sagan, B. Sabirov, В. Самолига, Yu. Semeney, А. Силаев, A. Silaev, Andrey Sidorenkov, Aleksandr Vasilevich Skurihin, V. Slunecka, A. Sokolov, C. Spiering, G. Spengler, L. Sveshnikova, В. А. Таболенко, B. Tarashansky, A. Tkachenko, Л. Ткачев, M. Tluczykont, А. Загородников, Д. Журов, В. Л. Зурбанов, I. V. Yashin

Bibliographic record

VenueProceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
FundersRussian Science FoundationRussian Foundation for Basic ResearchDeutsche ForschungsgemeinschaftEuropean CommissionMcGill University
KeywordsLidarRemote sensingLaserCalibrationOpticsPhysicsCherenkov radiationEnvironmental scienceDetectorGeology

Abstract

fetched live from OpenAlex

We report the first ground-based observation of the CATS-LIDAR onboard the ISS by the TAIGA-HiSCORE gamma-ray facility, and the MASTER-Tunka Robotic telescope. HiSCORE detects unscattered laser light directly from the ISS, at up to km-scale distance from the laser beam spot on ground. The ISS-LIDAR turns out to be a unique calibration tool, in particular to verify the absolute astronomical pointing of HiSCORE. We detected the LIDAR for 11 ISS-passages; among these were observations of forward scattering of the laser beam in dense clouds, which might carry information complementary to the LIDAR technique. We expect other air Cherenkov installations like IACTs to benefit from this light source.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
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 head0.015
GPT teacher head0.236
Teacher spread0.220 · 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.

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

Citations7
Published2017
Admission routes1
Has abstractyes

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