OMLeT—An Alternative Approach to Learning Metabolism: Glycolysis and the TCA Cycle as an Example
Bibliographic record
Abstract
The techniques and learning styles used by students to learn metabolism are as varied as the topics in biology. Given the technological advancement of computers, current resources (including textbook CDs and online Web sites) still fail to address the needs of all students, largely due to a psychological phenomenon called the hindsight bias. Personal experience expressed by undergraduates, verified the need for an additional resource, one that is interactive, simple, and informative. This resulted in the development of a Web site called OMLeT, an acronym for Online Metabolism Learning Tool. Through the use of PHP Hypertext Preprocessor (PHP) scripting, this project led to the creation of a dynamic Web site that is geared towards several aspects of learning styles and allows the student to process metabolic pathways via a user-defined approach. Furthermore, the versatility of the site provides the user with a comprehensive reference point. Currently, the site is constructed to contain two pathways, glycolysis and TCA cycle.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".