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Record W6930541695 · doi:10.5281/zenodo.14992375

From Relay-Based to DCS-Based Control: Technological Advancement in Industrial Automation.

2013· article· en· W6930541695 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2013
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsImpact
Fundersnot available
KeywordsAutomationIndustrial control systemControl systemMicroprocessorProgrammable logic controllerRelayControl (management)Supervisory control

Abstract

fetched live from OpenAlex

Industrial automation has evolved significantly, transitioning from early relay and contactor-based systems to modern microprocessor-based control. Early systems relying on relays and contactors were prone to human error due to the necessity of manual intervention. Microprocessor technology has enabled the development of Programmable Logic Controllers (PLCs), Supervisory Control and Data Acquisition (SCADA) systems, and Distributed Control Systems (DCS), which have dramatically reduced human intervention. This shift has resulted in greater accuracy, precision, and improved overall system efficiency. This paper provides a comparative analysis that demonstrates the benefits of adopting these modern technologies in today's industrial environments.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0120.005

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 head0.033
GPT teacher head0.248
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2013
Admission routes1
Has abstractyes

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