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Record W4393653948 · doi:10.5281/zenodo.10364776

A.E.G. G.IV - La Première Guerre mondiale

2017· dataset· fr· W4393653948 on OpenAlexaboutno aff
dtechnoscience

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typedataset
Languagefr
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesArtCombinatoricsMathematics

Abstract

fetched live from OpenAlex

Le bombardier Allgemeine Elektrizitäts Gesellschaft (A.E.G.) G.IV a été mis en service dans l'armée de l'air allemande en 1917. En raison de son rayon d'action court, il a surtout été utilisé pour des missions de bombardement tactique près du front. L'A.E.G. G.IV du Musée de l'aviation et de l'espace du Canada a été expédié au Canada comme trophée de guerre en 1919. C'est le seul avion allemand à plusieurs moteurs utilisé pendant la Première Guerre mondiale qui existe toujours. Remarque : Ce modèle est conçu pour être visualisé dans un environnement virtuel au moyen d'un logiciel. Vous pouvez tenter de l'imprimer. Toutefois, nous ne pouvons garantir la qualité. Pour prendre connaissance des activités éducatives permettant l'utilisation de ce modèle, visitez le site ingeniumcanada.org/ingenium/musees/educatif/avions-3D.php Vous trouverez nos conditions d'utilisation [ici](https://ingeniumcanada.org/ingenium/doc/content/cstmc/CSTMC%20terms%20of%20use%203D%20FR.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)0.001
metaresearch head score (Gemma)0.002
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 score0.270
Threshold uncertainty score0.904

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2700.121

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 head0.051
GPT teacher head0.242
Teacher spread0.191 · 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

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicFrench Historical and Cultural Studies→French-language works237,207→