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Record W2901601466 · doi:10.4000/palethnologie.885

Le plus ancien art mobilier : les statuettes aurignaciennes en ivoire du Jura souabe (sud-ouest de l’Allemagne)

2015· article· fr· W2901601466 on OpenAlexaff
Harald Floss

Bibliographic record

VenuePalethnologie · 2015
Typearticle
Languagefr
FieldArts and Humanities
TopicAncient and Medieval Archaeology Studies
Canadian institutionsYork University
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

Quatre grottes du Jura souabe ont livré un éventail spectaculaire d’art mobilier : Hohle Fels, Geißenklösterle, Vogelherd, et Hohlenstein-Stadel. Certaines de ces statuettes en ivoire sont bien connues, tandis que d’autres le sont moins. En tout, une cinquantaine de ces objets ou fragments ont été identifiés dans la région. Ils proviennent de niveaux archéologiques renfermant des instruments de musique (flûtes) et des témoignages anciens de peinture. En se basant sur des recherches récentes ainsi que sur les enregistrements de fouilles antérieures, cette contribution opte pour un format simple de questions-réponses afin de revisiter certains aspects de l’interprétation de l’art mobilier aurignacien. Certains de ces objets constituent les plus anciens artefacts figuratifs connus en Europe, et peut-être dans le monde. Les thèmes abordés ici comprennent des indications concernant les matières premières, l’iconographie, la datation, le contexte et les fondations sociales éventuelles de la production et de l’utilisation de ces objets.

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)0.003
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 score0.101
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0090.009
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.001

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 head0.054
GPT teacher head0.260
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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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