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Record W4394059078 · doi:10.5281/zenodo.10306191

A.E.G. G.IV - First World War Airplane

2017· dataset· en· W4394059078 on OpenAlexaboutno aff
technoscience d

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typedataset
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsAirplaneAeronauticsEngineeringAerospace engineering

Abstract

fetched live from OpenAlex

The Allgemeine Elektrizitäts Gesellschaft (A.E.G.) G.IV bomber went into general use with the German Air Force in 1917. Because of its relatively short range, the G.IV served mainly as a tactical bomber. The A.E.G. G.IV found at the Canada Aviation and Space Museum was transported to Canada in 1919 as a war trophy and has remained in the country ever since. It is the only surviving multi-engine German aircraft from the First World War and it is the only surviving aircraft from this period covered in the unique German "night lozenge" camouflage pattern. Note: This model is mainly meant to be viewed in a virtual environment using computer software. You can try printing it off, though we cannot guarantee the quality. For educational activities that this model can be used in, please visit: ingeniumcanada.org/ingenium/museums/education/3D-aircrafts.php Our terms of use can be found [here](https://ingeniumcanada.org/ingenium/doc/content/cstmc/CSTMC%20terms%20of%20use%203D%20ENG.pdf) Source: Objaverse 1.0 / Sketchfab

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)0.000
metaresearch head score (Gemma)0.001
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: Dataset · Consensus signal: none
Teacher disagreement score0.226
Threshold uncertainty score0.757

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2260.133

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 head0.037
GPT teacher head0.293
Teacher spread0.256 · 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
GenreDataset

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
Published2017
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicWorld Wars: History, Literature, and ImpactFrench-language works237,207