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Record W2156668337 · doi:10.1109/memsys.1998.659830

Micromachined accelerometer based on convection heat transfer

2002· article· en· W2156668337 on OpenAlexaff
Albert M. Leung, J.C. Jones, E. Czyzewska, Jun Chen, Brian Woods

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAccelerometerHeat transferMasking (illustration)ThermalSensitivity (control systems)ConvectionSurface micromachiningConvective heat transferAcousticsMaterials scienceMechanical engineeringComputer scienceElectrical engineeringEngineeringMechanicsElectronic engineeringPhysicsFabricationMeteorology

Abstract

fetched live from OpenAlex

A micromachined thermal accelerometer that is simple, reliable, and inexpensive to make has been developed at Simon Fraser University. The operating principle of this accelerometer is based on the free-convection heat transfer of a small hot air bubble in a sealed chamber. An experimental device that requires only four masking steps to fabricate has been built. This device has demonstrated a 0.6 milli-g sensitivity that can theoretically be extended to sub-micro-g level: A 2-axis accelerometer based on the same operating principle has also been fabricated and tested.

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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.194
Teacher spread0.178 · 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

Citations119
Published2002
Admission routes1
Has abstractyes

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