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Radio-frequency Interference Characterization and Mitigation for SARAS Experiment

2024· article· en· W4405676837 on OpenAlexaboutno aff
Girish Baragur Seshagiriyappa

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInternet of Things and Social Network Interactions
Canadian institutionsnot available
Fundersnot available
KeywordsInterference (communication)Radio frequencyCo-channel interferenceCharacterization (materials science)Electromagnetic interferenceComputer scienceAdjacent-channel interferenceElectronic engineeringTelecommunicationsPhysicsEngineeringOpticsChannel (broadcasting)

Abstract

fetched live from OpenAlex

From the Big Bang to the present, over the last 14 billion years, the Universe has undergone a series of crucial transformations.The emergence of the first stars and galaxies -called the Cosmic Dawn (CD) -and the subsequent ionization of the Universe, referred to as the epoch of reionization (EoR), constitute one such crucial period in cosmic evolution history.This period led to the formation of further structures that evolved into the Universe we see today.Very little is known about this crucial period due to the lack of observations.The 21-cm (1420 MHz) hyperfine transition of neutral hydrogen, redshifted to a frequency range of 40 MHz to 200 MHz from these cosmic times, has been recognized as an important probe of the physics of CD/EoR.Detection of this signal will provide insights into the properties of the first sources that lit up the Universe.Worldwide, there are several experiments to detect this elusive signal: SARAS (RRI, India), EDGES (US), PRIzM (Canada), High-z (US), and LEDA (US).In addition, several more experiments are being developed and commissioned.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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
Published2024
Admission routes1
Has abstractyes

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