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Record W3011737754 · doi:10.4000/pds.3699

Machines et outils de l’industrie aéronautique. Un patrimoine menacé, à Toulouse comme à Seattle

2020· article· fr· W3011737754 on OpenAlexaff
Jean-Marc Olivier

Bibliographic record

VenuePatrimoines du Sud · 2020
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsCanadian Heritage
FundersAgence Nationale de la Recherche
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article présente les menaces qui pèsent sur la conservation des outils et des machines de l’industrie aéronautique. En effet, cette activité récente et florissante n’a pas encore pris pleinement conscience de sa dimension historique et patrimoniale. Ses acteurs agissent parfois en ordre dispersé pour sauver ce qui peut l’être. Dans cet univers qui a le culte du secret, l’historien universitaire n’est pas toujours le bienvenu, à Toulouse comme à Seattle. Heureusement, il existe des associations dynamiques qui multiplient les initiatives afin d’éviter des pertes irréparables. Mais pour les périodes les plus anciennes, beaucoup de documents et d’objets manquent déjà à l’appel.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0060.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.250
Teacher spread0.206 · 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
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

Citations1
Published2020
Admission routes1
Has abstractyes

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