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Record W2215016318 · doi:10.1109/tcsii.2014.2304888

A 5-V 290- $\mu\hbox{W}$ Low-Noise Chopper-Stabilized Capacitive-Sensor Readout Circuit in 0.8- $\mu\hbox{m}$ CMOS Using a Correlated-Level-Shifting Technique

2014· article· en· W2215016318 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2014
Typearticle
Languageen
FieldEngineering
TopicAnalog and Mixed-Signal Circuit Design
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaAUTO21 Network of Centres of ExcellenceInstitute for Computing, Information and Cognitive SystemsCMC Microsystems
KeywordsCapacitive sensingChopperCMOSElectrical engineeringCapacitorCapacitanceAmplifierOperational amplifierSensitivity (control systems)PhysicsOptoelectronicsMaterials scienceElectronic engineeringEngineeringElectrodeVoltage

Abstract

fetched live from OpenAlex

In this brief, a low-power high-resolution readout front end intended for capacitive sensors is presented, in which the circuit uses correlated-level-shifting (CLS) and chopperstabilization (CS) techniques. CLS is a relatively new switchedcapacitor (SC) technique that is used to reduce errors from finite operational amplifier (op-amp) gain, whereas CS is a classic technique that is used to reduce the adverse effects of dc offset and low-frequency noise associated with the op-amp. In this brief, the capacitive sensor is physically emulated by a pair of on-chip differential variable capacitors that are in the femtofarad range. The proposed front end is designed in a 0.8-μm CMOS technology and consumes 290 μW from a single 5-V supply. The readout circuit achieves a capacitance noise floor of 0.018 aF/√Hz at 400 Hz with a sensitivity of 50 mV/fF.

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 score0.895
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.032
GPT teacher head0.222
Teacher spread0.190 · 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