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Record W2933108282 · doi:10.1017/s1743921319000395

The Arab Astronomical Society (ArAS): Developing Astrophysics Research in the Arab World

2018· article· en· W2933108282 on OpenAlexaff
Z. Benkhaldoun, R. Suleiman, Ismaël Moumen, Moza M. Al-Rabban, Randa Asa’d

Bibliographic record

VenueProceedings of the International Astronomical Union · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Products and Applications
Canadian institutionsUniversité Laval
FundersSmithsonian Astrophysical ObservatoryUniversité Cadi AyyadAl Akhawayn University in IfraneSmithsonian Institution
KeywordsHonourGeneral partnershipPolitical scienceWork (physics)EngineeringLawMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The Arab Astronomical Society (ArAS) was officially created during the constitutional assembly held in Marrakech (Morocco) on November 30, 2016, and legally recognized on May 15, 2017. ArAS is composed of a group of Arab researchers and students in the field of astrophysics who aim to develop research in this field in the Arab world (22 countries). ArAS is working on bridging the gap between the Arab astrophysicists in the Arab world and those around the world by organizing collaborative workshops and international scientific meetings, offering scholarships and developing graduate programs in astrophysics. Presently, the Society is working on establishing personal and material scientific infrastructure in the Arab world by training advanced undergraduate and graduate students in astrophysics and stimulating the building of new telescopes on the best sites in the Arab world. This will be accomplished through the hosting of specialized schools and conferences in astrophysics, international collaborations, facilitation of students’ and post-docs’ training in international research centres and universities, the establishment of prizes in astronomy to honour leading Arab scientists in astronomy and to motivate junior researchers to present notable works in astronomy. In this work, we present the on-going ArAS activities as well as future projects. ArAS is a young but energetic organization which is welcoming collaborations and partnership with other groups.

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)0.010
metaresearch head score (Gemma)0.005
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 score0.012
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0040.002
Scholarly communication0.0070.003
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.003

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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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
Published2018
Admission routes1
Has abstractyes

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