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Record W2595063396 · doi:10.1109/tmtt.2017.2671359

Design and Sensitivity Improvement of CMOS-MEMS Scanning Microwave Microscopes

2017· article· en· W2595063396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2017
Typearticle
Languageen
FieldEngineering
TopicNear-Field Optical Microscopy
Canadian institutionsRealNetworks (Canada)University of Waterloo
Fundersnot available
KeywordsMicroelectromechanical systemsMicrowaveSensitivity (control systems)CMOSMicroscopeMaterials scienceElectronic engineeringOptoelectronicsMicrowave engineeringElectrical engineeringComputer scienceEngineeringOpticsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

In this paper, we present the performance and imaging results of an integrated single-chip CMOS-microelectromechanical systems (MEMS) scanning microwave microscope (SMM). A systematic analysis for sensitivity improvement is described in detail. We first explain why it is important to have high sensitivity for this type of microscope and then propose a systematic method to analyze and design the entire structure for better sensitivity. For this, accurate lumped models are derived for each section of the system and comparisons are made between different designs. Furthermore, a new concept based on the quality factor of the individual sections is described to give the designer a tool to improve the sensitivity of individual sections without the need to simulate or model the entire system. A high-sensitivity measurement system is also explained. Finally some measurement results are presented. While the analysis presented in this paper is for CMOS-MEMS SMM, it is applicable to any type of SMM.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.012
GPT teacher head0.248
Teacher spread0.236 · 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