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Record W3034963701 · doi:10.1109/jproc.2018.2790278

Origins of the IEEE Edison Medal [Scanning Our Past]

2018· article· en· W3034963701 on OpenAlexaboutno aff
David P. Bart, Julia B. Bart

Bibliographic record

VenueProceedings of the IEEE · 2018
Typearticle
Languageen
FieldComputer Science
TopicHistory of Computing Technologies
Canadian institutionsnot available
FundersCharles Edison Fund
KeywordsMedalHonorEngineeringWork (physics)ManagementArt historyHistoryMechanical engineeringComputer science

Abstract

fetched live from OpenAlex

The Edison Medal is one of the most prestigious awards given in the United States and Canada recognizing meritorious accomplishments in the fields of electronics and electrical engineering. The year 2009 marked the 100th anniversary of this medal named in honor of America’s most famous inventor, Thomas Alva Edison. Edison’s work exemplifies the development of large scale industrial research laboratories, the creation of new technology, and the installation of the first complete electrical systems in the 19th century. For more than a century, many important contributors to the development of electronics have received the Edison Medal over its storied history. This article outlines the origins of the Edison Medal and its legacy of honor.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.009
Scholarly communication0.0110.007
Open science0.0010.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0110.005

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 head0.019
GPT teacher head0.247
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

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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

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