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Record W2243938698 · doi:10.12816/0009889

International Summer School on Islam and Science ( Paris , 22 - 31 August 2014 )

2014· article· en· W2243938698 on OpenAlexaboutno aff
Daud Abdul-Fattah Batchelor

Bibliographic record

VenueIslam and Civilisational Renewal · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicIslamic Studies and History
Canadian institutionsnot available
Fundersnot available
KeywordsIslamPolitical scienceMedia studiesHistorySociologyReligious studiesSocial scienceArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

An excellent program on Islam and Science was co-organised by Professors Nidhal Guessoum and Jean Staune (Director, Universitie Interdisciplinaire de Paris) in Paris for 21 Muslim ‘students’ from universities and institutions in Algeria, Egypt, Jordan, France, the United Arab Emirates, the United States and the United Kingdom, Indonesia and Malaysia. Professorial lectures were delivered by prominent Muslim scientists/engineers/religious scholars – Nidhal Guessoum (American University of Sharjah, UAE), Ehab Abouheif (McGill University, Canada), Bruno Guiderdoni (Islamic Institute of Advanced Studies in Paris), Odeh Jayyousi (Jordan), Usama Hasan (Quilliam Foundation, UK) and leading Christian scientists – Philip Clayton (Claremont School of Theology, USA), Denis Alexander (Faraday Institute, Cambridge, UK) and Jean Staune. This was a cutting edge program on the state of thinking on critical issues regarding Religion and Science. To support the training, group visits were made to the impressive institutions of the Museum National d’Histoire Naturelle and the Cite des Sciences et de l’Industrie, as well as to the Central Paris Masjid. The program was not all scientific as participants were also treated socially to warm French hospitality and delicious cuisine for their lunches and dinners.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.737
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.278
Teacher spread0.262 · 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 teacher head, 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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