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Record W4238554884 · doi:10.1109/ias.1989.96901

ESD characteristics of a generalized two body system including a ground plane

2003· article· en· W4238554884 on OpenAlexafffund
W.D. Greason

Bibliographic record

VenueConference Record of the IEEE Industry Applications Society Annual Meeting · 2003
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGround planeCapacitanceSink (geography)Electrostatic dischargeElectrical conductorPlane (geometry)MechanicsHuman-body modelPhysicsComputational physicsSimulationComputer scienceGeometryElectrical engineeringMathematicsEngineeringElectrodeQuantum mechanics

Abstract

fetched live from OpenAlex

Capacitance coefficients were measured for a system with two conductors of variable size, positioned at different elevations with respect to a horizontal ground plane. For a constant charge on the source, body potentials and energies were calculated and a comparison was made of the relative probability of a discharge and the severity of the discharge for the various source/sink geometries. Both a fixed-size source model and a fixed-size sink model were analyzed, for cases where the sink was floating or grounded. Positioning the bodies close to a horizontal ground plane decreases both the probability of a discharge and the severity of the discharge in all cases. Potential and energy sensitivity factors were calculated and used to show how the observed results can be interpreted using the changes in the capacitance coefficients of the system. The results provide a better understanding of the basic electrostatic discharge characteristics for simulations involving the human body model and the metallic cart model.>

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.257
Teacher spread0.238 · 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

Citations6
Published2003
Admission routes2
Has abstractyes

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Same venueConference Record of the IEEE Industry Applications Society Annual MeetingSame topicElectrostatic Discharge in ElectronicsFrench-language works237,207