Rethinking enzyme kinetics: Designing and developing a biomolecular interactive tutorial (BIOMINT) learning tool for undergraduate students
Bibliographic record
Abstract
Enzyme kinetics is the study of enzymatic catalytic rates in biochemical reactions. This topic is commonly taught to life science students in introductory biochemistry courses during their undergraduate education. Unlike most other biochemistry topics, which focus on visual structures of biomolecules and their processes, enzyme kinetics is explained primarily through abstract mathematical and two-dimensional graphical plots. However, these abstract/symbolic representations often make it difficult for students to relate the kinetic parameters to the underlying molecular system that is being described. In this article, we present the design and development of a web-based multimedia interactive learning tool, biomolecular interactive tutorials (BIOMINT) to help students better bridge the relationships between these abstract mathematical models and the molecular behaviors, interactions, and dynamics that produce kinetic phenomena. This learning tool can be accessed at https://bit.ly/biomint. © 2019 International Union of Biochemistry and Molecular Biology, 48(1):74-79, 2020.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".