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Record W2997474780 · doi:10.4000/culturemusees.4302

Réflexions sur la caractérisation et la catégorisation des maisons-musées en Espagne

2019· article· fr· W2997474780 on OpenAlexaff
Soledad Pérez Mateo

Bibliographic record

VenueCulture & Musées · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicHistorical Art and Architecture Studies
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesBiologyArt

Abstract

fetched live from OpenAlex

Notre domaine d’étude est la maison-musée en Espagne : nous en avons dénombré plus de 200, réparties sur 16 communautés autonomes, hormis celle de La Rioja, toutes analysées dans notre thèse doctorale (Pérez Mateo, 2016), à partir de laquelle nous chercherons, dans cet article, à définir des parallélismes ou des différences avec d’autres maisons-musées hors d’Espagne. Les deux variables employées sont la communauté autonome et la province à laquelle appartient chaque maison-musée, puis le pro...

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.006
Science and technology studies0.0030.007
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.012
GPT teacher head0.249
Teacher spread0.237 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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