Unlikely Sister Taxa - a Tree Drawing Activity That Facilitates Students' Understanding ofAnalogous and Homologous Structures
Bibliographic record
Abstract
The misconception that organisms with similar morphology are closely related is common among students. While students may memorize the definitions for analogous and homologous structures, many students find it difficult to understand how these terms relate to convergent and divergent evolution. This activity, which can be implemented into either lab or lecture, gives students an introduction to analogous and homologous structures as well as convergent and divergent evolution. It can also be used as a practice in tree thinking and an introduction to multiple sequence alignment. Students first predict the evolutionary relationship between six organisms by constructing a phylogenetic tree that they think best reflects the evolutionary relationship between them. Thereafter students verify their prediction by comparing DNA sequences using an online software. They then discuss reasons why their original prediction may not be correct. The activity can be expanded upon in several ways, which makes it suitable for introductory as well as upper level courses.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".