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The Story of Cavity Magnetron No. 12: Invited Paper

2024· article· en· W4399602330 on OpenAlexaffabout
David G. Michelson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCavity magnetronComputer scienceMaterials scienceOptoelectronicsNanotechnologyThin film

Abstract

fetched live from OpenAlex

In the summer of 1940, following the breakthrough work of John Randall and Harry Boot at the University of Birmingham earlier that year, cavity magnetron model E1189, serial no. 12 was assembled by Eric Megaw and his collaborators at GEC Laboratories in Wembley, UK. According to James Phinney Baxter III, Official Historian of the U.S. Office of Scientific Research and Development, “When the members of the Tizard Mission brought one to America in 1940, they carried the most valuable cargo ever brought to our shores.” The complete story of Cavity Magnetron No. 12, from the circumstances that led to its assembly at GEC Laboratories in Wembley to its pivotal role in the changing the direction of North American radar efforts during the Second World War to its current home at Ingenium in Ottawa, is widely dispersed amongst both published and unpublished sources. Here we present the results of our efforts to survey those sources, resolve some of the minor contradictions between various accounts, and add value to one of the most important items in Ingenium's collection.

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)0.003
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.003
Scholarly communication0.0080.004
Open science0.0010.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0110.006

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 head0.006
GPT teacher head0.198
Teacher spread0.192 · 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
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
Published2024
Admission routes2
Has abstractyes

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