Celebrating crystallography from K to 12 at CIMF, Montreal
Bibliographic record
Abstract
If crystallography is well known to many scientists, this is not true for the general public. Aims of the international year of crystallography include the desire to increase public awareness, to stimulate the intellectual curiosity of students and to promote crystallographic education. At the College International Marie de France, we decided to tackle these challenges and celebrate IYCR2014 with students from kindergarten to grade 10 and by an outreach with the Universite de Montreal (UdeM). We will illustrate how, beyond appreciating the mesmerizing ordered crystal growth from a saturated solution, studying and performing crystallization activities has a proven track record for fostering academic and practical skills. If crystallography starts by the Bragg's iconic law, then most undergraduate students will not appreciate it. However, crystals do have an intrinsic aesthetic appeal that can serve as a starting point to stimulate students' interest. Instead of teaching crystallography as a discipline, could we not teach key scientific concepts through it? We devised three distinct approaches addressing skills and notions appropriate to students in kindergarten, primary or grade 10 school levels. Younger pupils can make descriptions, comparisons and learn about symmetry and growth based upon the observation of snowflakes or crystal growth from solution, encouraging them to formulate basic concepts regarding solubility and changes in states of matter. Growing crystals allows primary students to practice mathematical skills such as measuring angles, masses, volumes and describing shapes. This sets the stage for problem solving using the scientific method. Older students take part in workshops ranging from diffraction patterns generated by lasers to simulating growth with cellular automata. They also undertake protein crystallization experiments in partnership with UdeM thereby offering unique access to crystallographic facilities and insight into scientific research.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.067 | 0.009 |
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".