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Record W2520969434 · doi:10.1021/acs.jchemed.6b00186

Applying Hand-Held 3D Printing Technology to the Teaching of VSEPR Theory

2016· article· en· W2520969434 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Chemical Education · 2016
Typearticle
Languageen
FieldChemistry
TopicVarious Chemistry Research Topics
Canadian institutionsUniversity of Victoria
FundersUniversity of Victoria
KeywordsConstruct (python library)Computer science3D printingNanotechnologyEngineeringMaterials scienceMechanical engineering

Abstract

fetched live from OpenAlex

The use of hand-held 3D printing technology provides a unique and engaging approach to learning VSEPR theory by enabling students to draw three-dimensional depictions of different molecular geometries, giving them an appreciation of the shapes of the building blocks of complex molecular structures. Students are provided with 3D printing pens and two-dimensional templates which allows them to construct three-dimensional ABS models of the basic VSEPR shapes. We found that the learning curve associated with manipulating the pen accurately and the time required to draw a structure is sufficiently high that this exercise would need to be limited in a laboratory setting to students each being tasked with drawing a different molecule; however, in the correct setting, hand-held 3D printing pens are a potentially powerful tool for the teaching of VSEPR theory.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.319
Teacher spread0.308 · 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