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Record W2024261776 · doi:10.1163/156798908x379675

Mysteries of the Nile? Joseph Scaliger and Ancient Egypt Les mystères du Nil? Joseph Scaliger et l'Égypte ancienne

2009· article· fr· W2024261776 on OpenAlexaff
Jitse H. F. Dijkstra

Bibliographic record

VenueAries · 2009
Typearticle
Languagefr
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesArtPhilosophyEthnologyHistory

Abstract

fetched live from OpenAlex

Abstract L'humaniste et savant Joseph Scaliger (1540–1609) est bien connu pour ses œuvres d'astronomie et de chronologies anciennes. Elles contiennent, notamment, des développements consacrés à ces domaines pour ce qui concerne l'Égypte ancienne. Cet article traite de la perspective adoptée par Scaliger sur l'Égypte ancienne, Dans quelle mesure cette perspective fut-elle influencée par l'“Égyptomanie” qui caractérise cette époque? En se fondant sur les œuvres et la correspondance de Scaliger, il s'agit de montrer que, même si son intérêt pour l'Égypte devait beaucoup à ses études en matière de chronologie et d'astronomie, il ne s'est pas limité à ces sujets. De fait, certains passages dans des lettres écrites par lui ou adressées à lui montrent que ses intérêts allaient au-delà. En raison de son approche philologique et de son érudition, ce savant s'est trouvé porté à considérer l'Égypte au même titre que n'importe quel autre pays de l'Antiquité. Aussi s'est-il trouvé en mesure de développer plusieurs idées originales sur l'Égypte ancienne, qui étaient très en avance sur son temps.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.011
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.017
GPT teacher head0.250
Teacher spread0.233 · 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 designTheoretical or conceptual
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
Published2009
Admission routes1
Has abstractyes

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