Numerical Modelling of C. elegans L1 Aggregation
Bibliographic record
Abstract
We attempt to explain the aggregation behavior of starved C. elegans L1s (Artyukhin et al., 2015) by a variation of the Keller-Segel chemotaxis model (1970). Each worm releases a diffusible, unstable attractant. The worms chemotax towards the attractant. By using a continuous density function to approximate the spatial distribution of worms, behavior may be described by a nonlinear system of partial differential equations. To determine whether such a model can account for C. elegans L1 behavior, we solve this PDE system numerically. In the original Keller-Segel model, density is unbounded, leading to unrealistic results. We modified the model in such a way as to limit the maximum density. We also developed numerical methods designed to work well near equilibrium. With these changes our model can reproduce some but not all aspects of the behavior.
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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".