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Record W4242658093 · doi:10.1021/cen-09435-newscripts

Interactive tools for teaching chemistryPeriodic table adds isotopes Augmented reality element blocks

2016· article· en· W4242658093 on OpenAlexaboutno aff
Linda Wang

Bibliographic record

VenueC&EN Global Enterprise · 2016
Typearticle
Languageen
FieldComputer Science
TopicEngineering Education and Technology
Canadian institutionsnot available
Fundersnot available
KeywordsAugmented realityTable (database)Computer scienceElement (criminal law)Human–computer interactionComputer graphics (images)MultimediaDatabasePolitical science

Abstract

fetched live from OpenAlex

Periodic table adds isotopes What comes to mind when you think about isotopes? Radioactivity, perhaps? That’s only the tip of the iceberg. A new interactive periodic table of the elements and isotopes, launched last month by the King’s Centre for Visualization in Science (KCVS) in Edmonton, Alberta, and the International Union of Pure & Applied Chemistry, aims to show the breadth of isotopes and their applications. “This is not going to replace the periodic table of the elements. It really is a periodic table of the elements that also provides, for the first time, really detailed information about the isotopes of the elements,” says Peter Mahaffy of the KCVS. In addition to the usual periodic table information of an element’s symbol, atomic number, and atomic weight, the new interactive version includes a pie chart that indicates how many isotopes an element has and their relative abundance. The development team hopes

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.467
Threshold uncertainty score0.761

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0020.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4670.165

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 head0.280
Teacher spread0.271 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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
Published2016
Admission routes1
Has abstractyes

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