"Got Algae?" A Sorting Game for Introducing the Weird and Wonderful Diversity of Algae
Bibliographic record
Abstract
Algae are a fascinating and diverse organismal group, with global ecological importance, a storied evolutionary history and deep connections to both contemporary and historical human societies. Yet non-experts who teach algal diversity face a lack of examples in many general biology textbooks and the difficulty of generalizing a group that includes many distantly-related lineages that don't share a single common ancestor. This lesson embraces the complexity of algae using a sorting game and tree-building activity. Students work in groups to decide which organisms from a provided set are eukaryotic algae. The class creates consensus statements about what exactly defines organisms as "algae" and self-discover that exceptions exist for every seemingly definitive algal trait. Students then build simple phylogenetic trees and map their organisms across the phylogenetic Tree of Eukaryotes in order to explore the complex evolutionary relationships between the major eukaryotic algal lineages. Student written responses recorded before and after the sorting game indicate students become more nuanced and expert-like in their descriptions of algae. This lesson is an engaging way to introduce students to algae and can be modified for a variety of courses including high school, non-majors biology courses and introductory biology courses. Primary image: A photo of the phylogenetic trees made by students during the tree-building activity. Photo taken by the author, B. Clarkston.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.069 | 0.015 |
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".