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Record W3110669900

Interferometric calibration and the first elevation observations at EKB ISTP SB RAS radar at 10–12 MHz

2021· article· en· W3110669900 on OpenAlexaff
O. I. Berngardt, Roman Fedorov, K. V. Grkovich

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
FundersRussian Foundation for Basic Research
KeywordsMeteor (satellite)Remote sensingCalibrationElevation (ballistics)RadarWaveformInterferometryMeteoroidGeologyEnvironmental scienceMeteorologyPhysicsComputer scienceOpticsTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

The method for calibrating elevation measurements at EKB ISTP SB RAS radar obtained for the period 20/09/2019–18/11/2019 is presented. The calibration method is a modernization of the method for calibrating radar by meteor trails. The main difference of the method is the use of not a statistically processed FitACF data, but the full waveform of the signals scattered on the meteor trails. Using the full waveform makes it possible to more reliably distinguish meteor scattering from other possible scattered signal sources, and to determine meteor heights from the trail lifetime using the NRLMSIS-00 model. A comparison of the results with the results of E-layer calibration method shows a good agreement. The first examples of regular elevation observations at the EKB ISTP SB RAS radar are presented, and their preliminary interpretation is given.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.014
GPT teacher head0.216
Teacher spread0.203 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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