MétaCan
Menu
Back to cohort
Record W2613764918 · doi:10.1109/tmtt.2017.2697383

Fast Quantitative Microwave Imaging With Scattered-Power Maps

2017· article· en· W2613764918 on OpenAlexafffund
Denys S. Shumakov, Natalia K. Nikolova

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrowave imagingInversion (geology)ScatteringNonlinear systemIterative reconstructionMicrowaveCalibrationInverse scattering problemComputer scienceIterative methodOpticsAlgorithmPhysicsTelecommunicationsGeologyArtificial intelligence

Abstract

fetched live from OpenAlex

A new direct-inversion method, scattered-power mapping (SPM), for fast quantitative microwave imaging is introduced. It builds on a recently proposed inversion strategy that demonstrated quantitative direct reconstruction with experimentally acquired system point-spread functions. In comparison with this initial work, SPM features a drastic improvement in the computational time along with reduced number of calibration measurements. Moreover, SPM is versatile allowing a forward model of scattering cast either as a linearized Born model or as a Rytov model. SPM is intended as a tool to solve weak-scattering problems or as a linear-inversion module within nonlinear iterative reconstruction.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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 designSimulation or modeling
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

Citations45
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on Microwave Theory and TechniquesSame topicMicrowave Imaging and Scattering AnalysisFrench-language works237,207