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Record W6968716107 · doi:10.5281/zenodo.7068465

Ground based meteor radar of Kazan Federal University

2022· article· en· W6968716107 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstro and Planetary Science
Canadian institutionsnot available
Fundersnot available
KeywordsMeteor (satellite)MeteoroidRadarMeteor showerAtmosphere (unit)InterferometryRadar systems

Abstract

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Currently, sources of meteor particles that fall into the upper atmosphere when the Earth moves in its orbit are being actively investigated. For this, the radiometric method is very actively used. This method is based on the radiolacation of meteor trails that appear as a result of the ionization of air in the mesosphere – the lower thermosphere (75-110 km) during the combustion of meteors. Radiometric observations of meteor showers are actively conducted at Kazan Federal University. Regular observations began in 1978, and the first data measuring the heights of meteor combustion began in 1985. In 2015, a Skiymet-type meteor radar of joint Canadian and Australian production was installed. The KFU meteor radar consists of a phase interferometer (five two-element crossed receiving antennas of the Yagi-Udo type) with bases of wavelengths 2 and 2.5, a transmitting antenna (crossed three-element antennas), as well as a transmitter with a power of 15 kW per pulse (average power of about 1 kW) with a carrier frequency of 29.75 MHz and a pulse repetition frequency of 1594 Hz. The meteor radar of Kazan Federal University (56N, 49E) is constantly being upgraded. The results of modernization are presented: a significant increase in the number of meteors and the accuracy of the estimation of angular coordinates and heights.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.019
GPT teacher head0.195
Teacher spread0.176 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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