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Record W3154690727 · doi:10.4000/anabases.12273

Lisa Maurice, Screening divinity

2021· article· en· W3154690727 on OpenAlexaff
Mathieu Scapin

Bibliographic record

VenueAnabases · 2021
Typearticle
Languageen
FieldArts and Humanities
TopicArchaeology and Historical Studies
Canadian institutionsMusée de la Civilisation
FundersInstitut d'Estudis CatalansDe La Salle University
KeywordsDivinityHumanitiesArtPhilosophyArt historyTheology

Abstract

fetched live from OpenAlex

La très prolifique série de publications « Screening Antiquity », publiée chez Edinburgh University Press, a accueilli en juin 2019 la monographie de Lisa Maurice, professeure et spécialiste de la réception de l’Antiquité de l’Université Bar-Ilan (Israël), Screening Divinity. Il s’agit d’un ouvrage s’intéressant à la représentation du divin à l’écran, que ce soit dans les traditions gréco-romaine ou judéo-chrétienne. Cette démarche est plutôt novatrice car elle a été peu abordée dans son ense...

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)0.002
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.036
Threshold uncertainty score0.120

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0080.003
Scholarly communication0.0070.006
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0360.013

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 head0.064
GPT teacher head0.244
Teacher spread0.180 · 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
Published2021
Admission routes1
Has abstractyes

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