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Record W4221041662 · doi:10.5194/egusphere-egu22-10429

HF scintillation in the high-latitude ionosphere

2022· preprint· en· W4221041662 on OpenAlexaboutno aff
G. W. Perry, Leslie Lamarche, Binjie Liu

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsScintillationIonosphereInterplanetary scintillationBackscatter (email)RadarHigh frequencyRadio wavePhysicsRemote sensingEnvironmental scienceGeologyGeophysicsMeteorologyTelecommunicationsComputer scienceOpticsSolar wind

Abstract

fetched live from OpenAlex

In this presentation we will report on the first results of a multi-year study of high frequency (HF; 3-30 MHz) radio scintillation in the North American sector of the high-latitude ionosphere. We will focus on HF signals collected by the Radio Receiver Instrument (RRI) onboard the CASSIOPE spacecraft (also known as Swarm-E) during coordinated experiments between RRI the Super Dual Auroral Radar Network (SuperDARN) systems located at Saskatoon, Rankin Inlet, and Clyde River (all in Canada). The investigation's goals are to use the RRI data from the SuperDARN experiments to specify the nature of HF scintillation in the region, diagnose scintillation caused by ionospheric irregularities and distinguish it from scintillation resulting from HF radio propagation effects, identify geophysical phenomena responsible for HF scintillation, and ascertain the relationship (if any) between HF scintillation and backscatter measured by the SuperDARN systems.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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 designObservational
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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