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Record W1491554238 · doi:10.3917/docsi.512.0030

1. Le document au cœur de l'organisation muséale

2014· article· fr· W1491554238 on OpenAlexaff
Maryse Rizza, Corinne Barbant, Patrick Le Bœuf, Stéphanie Fargier-Demergès

Bibliographic record

VenueDocumentaliste-Sciences de l Information · 2014
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsDocumentationChristian ministryFunction (biology)Principal (computer security)Knowledge managementSociologyDiversity (politics)Library sciencePolitical scienceAnthropologyComputer scienceLaw

Abstract

fetched live from OpenAlex

Our opening section concerns the role of documentation in an organization - its actors, processes, objects, forms, supports and standards - to further enhance our understanding of the role of documentation and the principal stakes in the shift to computerization, in particular in museum organizational processes.It is only recently that information professionals have taken on a key role in museums. Although three specific roles were established by the Cultural Ministry in 1978, they differ from one establishment to the next. Such organizational diversity at the heart of museums illustrate just how specific this function is.

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)0.003
metaresearch head score (Gemma)0.010
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: none
Teacher disagreement score0.064
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0050.003
Scholarly communication0.0140.005
Open science0.0010.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0640.028

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 head0.102
GPT teacher head0.313
Teacher spread0.211 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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