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Record W2108643792 · doi:10.1109/icmens.2004.1508953

An Integrated Test Platform for Nanostructure Electrical Characterization

2006· article· en· W2108643792 on OpenAlexafffund
O. Duval, L.-P. Lafrance, Yvon Savaria, P. Desjardins

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsRegroupement Québécois sur les Matériaux de PointePolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCMOSCapacitanceInductanceChipIntegrated circuitVoltageMaterials scienceElectronic engineeringElectronicsElectrical engineeringCharacterization (materials science)Parasitic capacitanceParasitic elementComputer scienceOptoelectronicsEngineeringNanotechnologyPhysics

Abstract

fetched live from OpenAlex

We have designed and fabricated a fully-integrated CMOS-based lab-on-a-chip electronics platform to investigate the electrical characteristics of novel nanoelectronic devices. In contrast with previous work which requires the use of external equipment, therefore limiting the range of possible measurements due to parasitic capacitance and inductance, we embed the nanostructures on an integrated circuit produced with a mature 180-nm CMOS process. The test platform includes modules for measuring I-V curves with a driven current range from 100 pA to 100 µA, and a measured voltage in the 0-1.5 V range. Propagation delay measurement modules as fine as 7 ps are also included. Inputs-outputs and test configurations are controlled using a standard IEEE 1149.1 JTAG scan chain.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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

Citations0
Published2006
Admission routes2
Has abstractyes

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