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Record W1514835229 · doi:10.1109/icsens.2003.1279140

Intelligent digital thermal flow sensor

2004· article· ca· W1514835229 on OpenAlexafffund
F. Yiu, Guangjun Liu

Bibliographic record

Venuenot available
Typearticle
Languageca
FieldComputer Science
TopicSensor Technology and Measurement Systems
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnemometerThermistorCompensation (psychology)Electronic engineeringPulse-width modulationDigital signalComputer scienceSIGNAL (programming language)ElectronicsModulation (music)Temperature measurementElectrical engineeringDigital signal processingVoltageEngineeringAcousticsPhysicsWind speed

Abstract

fetched live from OpenAlex

In the present work, most of the original analog circuit of a conventional hot-wire anemometer is replaced with digital electronics, and a signal prediction algorithm is implemented to speed up the sensor measurement. This digital sensor also includes the following upgraded features: (1) temperature compensation over the nonlinearity characteristics of thermistors to achieve more accurate measurement, (2) direct interface to computer, (3) easy change of operational parameters and sensor configurations, and (4) energy conservation with the use of a Pulse Width Modulation (PWM) heater.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.030
GPT teacher head0.236
Teacher spread0.205 · 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

Citations5
Published2004
Admission routes2
Has abstractyes

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