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Record W4388855111 · doi:10.1109/mias.2023.3329292

Demystification of Arc-Fault Circuit-Interrupters: Part I: Beginning of the Odyssey

2023· article· en· W4388855111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueIEEE Industry Applications Magazine · 2023
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsnot available
Fundersnot available
KeywordsOvercurrentElectric arcArc-fault circuit interrupterShort circuitElectrical engineeringCurrent (fluid)Arc (geometry)Fault (geology)EngineeringNational Electrical CodeCircuit breakerForensic engineeringVoltageMechanical engineeringGeologyElectrodePhysics

Abstract

fetched live from OpenAlex

Residential fires of electrical origin have been a major concern for a long time. A fire can be initiated by excessive current (due to an overload or a short circuit) or arcing current. Therefore, both the Canadian Electrical Code (CE Code) Part I and the National Electrical Code (NEC) require the installation of overcurrent protection devices (OCPDs) to detect and clear excessive current. Conversely, arcing current is too low for OCPDs to detect. It could take an electric arc minutes, days, weeks, months, or even years to initiate a fire. Therefore, a new solution was required for detecting those slowly developing arcs. Thus, arc-fault circuit-interrupters (AFCIs) were born. AFCIs are capable of detecting an arcing condition (while still developing) and de-energizing the circuit before the arcing circuit ignites.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.261
Teacher spread0.228 · 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