Fly Exercise: A Simple Experiment to Test the Physiological Effects of Exercise on a Model Organism
Bibliographic record
Abstract
Model organisms are commonly used to study and experimentally explore biological processes in ways that are technically or ethically not possible in humans. For this reason, model organisms are an essential component of scientific research and exposing students to practical applications of data collection using model organisms is an essential component of a thorough scientific education. In this paper, we use the fly model species, Drosophila melanogaster, and a fly treadmill to perform an exercise physiology experiment. The goal of the experiment is to expose students to the process, value, and importance of using model organisms in scientific research. The instructor will assist students in collecting, exercising, and sacrificing the flies from various lines and sexes. The students will quantify a biologically meaningful suite of enzyme activities and metabolite concentrations, assemble the results from the assays in a spreadsheet document, plot the data from the results and perform statistical analyses to quantify and, finally, graphically present physiological changes associated with the different exercise regimes. The experiment can be conducted in two three-hour sessions; the first to collect, exercise, and homogenize the flies and then perform enzymatic kinetic assays, the second to quantify metabolite concentrations. After the second lab session, the students will have the complete experimental data set and will be able to perform data analysis on their results. The experiment is designed to suit second to fourth year undergraduate students, depending on their past laboratory experience and skillset.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".