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Record W2557360299 · doi:10.1107/s2053273314086823

The International Year of Crystallography in the Americas

2014· article· en· W2557360299 on OpenAlexaboutno aff
Martha M. Teeter

Bibliographic record

VenueActa Crystallographica Section A Foundations and Advances · 2014
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsOutreachLatin AmericansPoliticsLibrary sciencePolitical sciencePublic relationsComputer scienceLaw

Abstract

fetched live from OpenAlex

The American Crystallographic Association has focused its celebration of IYCr principally on outreach to spread the message of the importance of crystallography in our daily lives and to attract young people into science. We have formed an Ad Hoc Task Force, representing 13 geographical regions of 100-200 members each to develop our goals, to coordinate events and to enable specific activities. Key to our activities are a website which offers an attractive link for young scientists, projects and teaching tools for schools, biographies of important crystallographers, an adopt a crystallographer link, and video and crystal growing contests. We have continued to send scientists to Latin America for training workshops and assist Latin Americans in attending the ACA meetings. In order to create a lasting legacy for the International year, we have worked closely with national organizations such as in the US the National Science Teachers Association, the American Chemical Society, the American Institute of Physics, as well as student outreach groups like the Society for Physics Students. Forging an ongoing relationship with these organizations will aid our continuing outreach. Similar organizational contacts have been made in Canada and in Latin America. Working with national organizations can also help to influence the political climate for science funding.

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)0.004
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 score0.075
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0050.003
Scholarly communication0.0120.004
Open science0.0010.007
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0750.016

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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
Published2014
Admission routes1
Has abstractyes

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