MétaCan
Menu
Back to cohort
Record W7000836447

The historical evolution of the DC Current Transformer (DCCT)

2024· other· en· W7000836447 on OpenAlexaboutno aff

Bibliographic record

VenueCERN Document Server (European Organization for Nuclear Research) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCurrent (fluid)Current transformerTransformerMagnetDirect currentVoltage
DOInot available

Abstract

fetched live from OpenAlex

The DCCT (DC Current Transformer) is a measurement transformer, today a mature product, available from industry, using technologies based on the zero-flux principle. This paper retraces the history of its development as promoted in different measurement fields. There were two distinct paths of development, originating in very different requirements and objectives. The first one was for increased accuracy in testing AC current transformers resulting in the Current Comparator developed at Nikola Tesla Institute, Belgrade, Serbia and NRC, Ottawa, Canada in the end of the 1950s and beginning of the 1960s. This concept was extended to DC measurements. The second area was for the need of magnet current control and proton beam current measurements in accelerators at CERN, Geneva, Switzerland in 1961-62, later resulting in the development of the zero-flux DCCT for magnet current control in accelerators.

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)0.004
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0010.008
Scholarly communication0.0060.007
Open science0.0020.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0060.004

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 head0.027
GPT teacher head0.278
Teacher spread0.251 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCERN Document Server (European Organization for Nuclear Research)French-language works237,207