High-impact crystallography skills development through local undergraduate curriculum and regional workshops and schools
Bibliographic record
Abstract
Resources to develop high impact skills in diffraction data collection and interpretation can be limited by facility access, expert availability, and the budgetary requirement to meet a critical mass of participants before it becomes practical to offer instruction. At the local level, shared resources between institutions, as well as curriculum approaches that incorporate scaffolding practices from first year general chemistry to senior undergraduate capstone courses, can be employed to equip trainees with skills in structural science. [1] Looking to the regional and (inter)national level, the Canadian National Committee for Crystallography (CNCC) [2] sponsors the annual Canadian Chemical Crystallography Workshop (CCCW) and the Canadian Powder Diffraction Workshop (CPDW), both which have now past their first decades of instruction. Several hundred trainees from Canada, and well beyond (for example, the US, UK, and Brazil) have participated in these opportunities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".