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Record W7051685321

Oral History Interview with Ward McGill, January 23, 2008

2008· article· en· W7051685321 on OpenAlexaboutno aff

Bibliographic record

VenueThe Portal to Texas History (University of North Texas) · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsInfantryOral historyWorld War IIGeorge (robot)HundredthFirst world war
DOInot available

Abstract

fetched live from OpenAlex

The National Museum of the Pacific War presents an interview with Ward McGill. McGill joined the Army in June of 1943. He completed boot camp at Camp Abbot in Oregon. He trained as a Combat Engineer, building Bailey bridges and pine log bridges. He provides great details of his training. He was assigned to Company B, 66th Armored Infantry Battalion, 12th Armored Division. Around September of 1944 they traveled to England where McGill worked as an assistant squad leader, driving a half-track. In November they landed at Le Havre, France, supporting the 94th Infantry Division up to the banks of the Rhine River, enduring numerous attacks and casualties of fellow servicemen. McGill was wounded in April of 1945 by a sniper near Würzburg, Germany. He was discharged in 1945.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.158
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1580.026

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 head0.030
GPT teacher head0.206
Teacher spread0.176 · 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 designQualitative
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

Citations0
Published2008
Admission routes1
Has abstractyes

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