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Record W2903483579 · doi:10.1109/estc.2018.8546339

Printed Flexible FE Memory Array Testing System

2018· article· en· W2903483579 on OpenAlexaff
Shoude Chang, Yanguang Zhang, Badrou Réda Aïch, Ye Tao

Bibliographic record

Venue2018 7th Electronic System-Integration Technology Conference (ESTC) · 2018
Typearticle
Languageen
FieldEngineering
TopicElectrowetting and Microfluidic Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsLaptopReading (process)Computer scienceComputer hardwareEmbedded systemSoftwareCapacitorOperating systemElectrical engineeringEngineeringVoltage

Abstract

fetched live from OpenAlex

In this paper, a compact testing system is developed to read/write a printed flexible FE (Ferroelectric) memory arrays and evaluate individual FE capacitors. Novel technologies, to the best of our knowledge, for random cell accessing, reading/writing,and analyzing are achieved. This compact system (both hardware and software) is controlled by LabVIEW program installed in a Laptop,and is essentially multi-functional and programmable. This system is designed for writing/reading FE memory cells, individually or in batch, as well as analyzing and displaying FE memory.

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)0.001
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 score0.554
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.015
GPT teacher head0.218
Teacher spread0.203 · 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.

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
Published2018
Admission routes1
Has abstractyes

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