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Record W2102905528 · doi:10.1109/19.893264

A generic automated/semiautomated digital multi-electrode instrument for field resistivity measurements

2000· article· en· W2102905528 on OpenAlexfundno aff
Dale Werkema, Eliot A. Atekwana, William A. Sauck, Johnson Asumadu

Bibliographic record

VenueIEEE Transactions on Instrumentation and Measurement · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysical and Geoelectrical Methods
Canadian institutionsnot available
FundersUniversity of WaterlooWestern Michigan University
KeywordsModular designData acquisitionInterface (matter)ElectrodeSoftwareComputer scienceElectrical engineeringField (mathematics)Electronic engineeringComputer hardwareEngineering

Abstract

fetched live from OpenAlex

The objective of this work is to design and test a digital multi-electrode acquisition system for use in geophysical investigations utilizing direct current electrical (geoelectric) methods. The system is a 64-electrode modular system, which utilizes field electrodes with individual wires that lead back to a digital switch box and then to a data acquisition instrument (Iris Syscal R2). The electronic design allows for different arrays or geometrical switching configurations of the field electrodes in order to allow for rapid data reading and yield essentially real-time results. Additionally, the electronic switch box has the capability to be connected in series to similar switch boxes and, therefore, has the ability to switch between an unlimited number of electrodes. The acquisition control software, developed as an interface for the hardware, controls operation of both the digital switch box and the resistivity acquisition instrument.

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)0.002
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: Methods
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.004

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 head0.066
GPT teacher head0.276
Teacher spread0.210 · 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
GenreMethods

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

Citations8
Published2000
Admission routes1
Has abstractyes

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