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CMOS Capacitive DNA Nano-Mass Measurement for DNA Storage Application

2021· article· en· W3208478051 on OpenAlexaff
Hamed Osouli Tabrizi, Saghi Forouhi, Morteza Ghafar-Zadeh, Sebastian Magierowski, Ebrahim Ghafar‐Zadeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsYork University
Fundersnot available
KeywordsCMOSCapacitive sensingCapacitanceMaterials scienceChipOptoelectronicsSensitivity (control systems)Electronic engineeringElectrical engineeringEngineeringPhysicsElectrode

Abstract

fetched live from OpenAlex

In this paper, we present, for the first time, the advantage of CMOS capacitive sensor for the assessment of dried DNA from an aqueous sample for DNA storage applications. The proposed capacitive sensor consists of a differential capacitance to current converter block based on a core-CBCM circuit, a 300 MHz current controlled oscillator and a 12-bit counter that creates the digital output of the chip. The chip has been fabricated using AMS 0.35µm technology. We demonstrate the functionality and applicability of the proposed sensor for dried DNA nano-mass measurement using single-strand DNA samples. The sensor shows acceptable repeatability in quantifying the DNA nano-mass with a sensitivity of 18.5 aF/ng mass of DNA based on the results described here.

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)0.001
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.016
GPT teacher head0.264
Teacher spread0.248 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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