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Record W3117651168 · doi:10.1109/bibe50027.2020.00087

Microwave-based Nondestructive Sensing Approach for Blood Type Identification

2020· article· en· W3117651168 on OpenAlexafffund
Ala Eldin Omer, George Shaker, Richard L. Hughson, Safieddin Safavi‐Naeini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsResearch Institute for AgingUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrowaveDielectricMaterials scienceNetwork analyzer (electrical)RadarCoaxialSpectrum analyzerABO blood group systemOptoelectronicsOpticsElectronic engineeringComputer scienceTelecommunicationsPhysicsEngineeringMedicine

Abstract

fetched live from OpenAlex

This study reports the in-vitro characterization of blood samples based on the dielectric property measurements across the microwave spectrum 2 - 67 GHz using a newly developed commercial coaxial probe kit. This is done for different ABO-Rh types of synthetic blood samples as well as authentic specimens drawn from healthy adult donors. Measured results have indicated an appreciably dielectric contrast between blood samples of various types at certain frequency regions. This phenomenon is also demonstrated by the resonant measurements on a novel developed CSRR-based biosensor in the centimeter-band using two different setups of Vector Network Analyzer and 2.45 GHz radar board.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.035
GPT teacher head0.220
Teacher spread0.186 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations5
Published2020
Admission routes2
Has abstractyes

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