Inexpensive Open Source Laser Cut Model Kits for the Teaching of Molecular Geometry
Bibliographic record
Abstract
We recently published an article in the Journal of Chemical Education on VSEPR model kits for helping teach molecular geometry. We have used these transparent acrylic models for several years now at the University of Victoria, but the challenges of COVID-19 meant that this year we needed to make a faster, less expensive version that could be easily mailed out to our students, without requiring any sorting and packaging steps. Accordingly, we designed a version that can be cut out of 2 mm thick recycled “chipboard” cardboard, in which all 26 parts for the 13 different models fit in one piece of card 175 × 120 mm (and 16 of these kits can be cut from one sheet in the laser cutter). The material cost is less than $0.25 per kit and the cutting time on our machine (Trotec Speedy360, 130 W) is 1 minute and 45 seconds per kit. These files are made freely available for all interested users as supporting information for this contribution, in CorelDraw, Adobe Illustrator, pdf and dxf formats.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.191 | 0.086 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".