Box of Lessons: An Open Educational Resource for Exploring Biomolecular Structure and Function
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.
Bibliographic record
Abstract
Structure-function relationships are a core concept in many STEM disciplines. Most biology curricula introduce students to macromolecules, their building blocks, and other small molecules that play key roles in biological processes. However, the shapes, interactions, and functions of these molecules are often discussed using schematic diagrams, ignoring the vast amounts of three-dimensional structural and bioinformatics data freely available from public data resources. Keeping up with and incorporating the rapidly evolving data, tools, and resources in suitable, structure-function focused lessons can be time-consuming and challenging. A group of experienced biology, chemistry, and biochemistry educators collaboratively developed the "Box of Lessons" (BOL) to engage students and educators in authentic explorations, reinforcing disciplinary concepts, while developing skills in biomolecular visualization and use of public bioinformatics data resources and tools. The BOL consists of multimedia learning materials, ready-to-use, student- and educator-facing worksheets with teaching notes, aligned with ASBMB learning goals. Materials in this collection have been reviewed and piloted by undergraduate educators before its publication on PDB-101, as modular open educational resources. Educators are encouraged to select BOL elements relevant to their curricular context and adapt them to fit their students' needs and learning goals.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it