A cell fate mapping simulation laboratory to increase undergraduate students’ understanding of early developmental processes in frog, zebrafish, and tunicate embryos
Bibliographic record
Abstract
ABSTRACT Fate mapping is an essential technique in developmental biology that allows researchers to track the future identity or “fate” of embryonic cells in an organism. However, the experimental procedure for constructing fate maps is tedious, time-consuming, and technically challenging, making it difficult to incorporate as an undergraduate lab experience. Here, we describe a hands-on undergraduate laboratory activity that allows students to generate and examine model organisms’ fate maps, employing a free, user-friendly web-based app, FatemapApp ( http://fatemapapp.com/ ). Students used the app to construct the fate maps for the 32-cell stage Xenopus laevis frog embryo, the gastrula stage Danio rerio zebrafish embryo, and the 76-cell stage Holocynthia roretzi tunicate embryo. Individual analysis of the maps allows students to identify the potential of cells to contribute to one or multiple tissues and their probability of moving and mixing with the neighboring cells. Subsequently, cross-species comparative analysis allows students to infer tissue organization across chordate and vertebrate embryos that may be evolutionarily conserved. Surveys showed that the students found this activity engaging and valuable, reporting a deeper understanding of the rationale, methodology, and outcomes underlying the construction of fate maps. Furthermore, students reported increased comprehension of embryonic development and its processes.
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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".