Episode 091: How stealth organs make super soldier ants (with Rajee Rajakumar)
Bibliographic record
Abstract
What is eco-evo-devo? How can ants help us understand the evolution of development? There are 20 quadrillion ants in the world, and they come in lots of different shapes and sizes. We even see big differences within colonies, like ants in the genus Pheidole which have different castes: workers, soldiers, and, in some species, super soldiers. Super soldiers are the muscle-y brutes of the ant world that grow huge heads to defend the colony and attack large food items, like other insects. This variation is all due to developmental plasticity – the same ant genotype produces distinct phenotypes depending on the environment of their early lives. On this episode, we talk with Rajee Rajakumar, a professor at the University of Ottawa, who studies Pheidole ants to understand the interactions between their genes, their developmental environments, and their phenotypes. Rajee is also a HUGE ant fan! We talk with him about his 2018 paper in Nature about the mysterious organs that control these differences in development, and amazingly, how these organs could be socially regulated via pheromones. Cover photo: Keating Shahmehri
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.168 | 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".