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Record W4294990915 · doi:10.48550/arxiv.1708.09309

Particle Physics Masterclasses for the International Day of Women and\n Girls in Science

2017· preprint· W4294990915 on OpenAlexaff
Julia Isabell Djuvsland

Bibliographic record

VenuearXiv (Cornell University) · 2017
Typepreprint
Language
FieldSocial Sciences
TopicInternational Science and Diplomacy
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsOutreachWomen in scienceLibrary scienceLarge Hadron ColliderPolitical sciencePhysicsSociologyGender studiesParticle physicsComputer science

Abstract

fetched live from OpenAlex

On the occasion of the UN International Day of Women and Girls in Science\n(February 11) Masterclass activities were launched by the International\nParticle Physics Outreach Group to support and promote the access of women and\ngirls to science education and research activities. Universities and research\nlaboratories organised 10 Masterclasses for girls on February 10 and 11, with\nparticipation from Barcelona, Cagliari, Cosenza, Heidelberg, Madrid, Paris,\nPrague, Rio de Janeiro, and Sao Paulo. About 300 girls participated in the\nevents and analysed LHC data while being tutored by female scientists. Three\nvideo conferences with CERN were held where the girls could talk to CERN women\nscientists and learn about the careers of these role models.\n

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)0.006
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.094
Threshold uncertainty score0.316

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0180.003
Scholarly communication0.0070.003
Open science0.0010.010
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0940.024

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 head0.127
GPT teacher head0.276
Teacher spread0.150 · 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
GenreOther

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

Citations1
Published2017
Admission routes1
Has abstractyes

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