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Record W7038754290

Investigation of a micromachined electric field mill to maximize the electrostatic field sensitivity

2012· dissertation· en· W7038754290 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2012
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicDate Palm Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSurface micromachiningFinite element methodShutterElectric fieldSensitivity (control systems)Field (mathematics)Fabrication
DOInot available

Abstract

fetched live from OpenAlex

This thesis includes the modification and optimization to an electric field mill based on micromachining technology. The sensor was originally designed to overcome the disadvantages of the conventional macroscopic field mill. Although it achieved all these listed above with a minimum detectable field strength at 42 V/m, some drawbacks are yet to be settled. In order to overcome these drawbacks, modifications are studied and put forward. Metal coating of the sensor surface could lead to a good electrical grounding that addresses the charging problem. Non-resonant working design was established with a shutter displacement around 5μm. Finite element simulations were set up to look into the optimizations of the structure parameters of the sensor, focusing on the shutter and electrodes. Moreover, the fabrication process was also studied with attempts of each step carried out in the NSFL of University of Manitoba.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.880
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.213
Teacher spread0.195 · 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.

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

Citations1
Published2012
Admission routes1
Has abstractyes

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