DevoWorm: differentiation waves and computation in C. elegans embryogenesis
Bibliographic record
Abstract
Abstract Development is a complex process that, under normal circumstances, proceeds in a stable and patterned fashion. Developmental morphogenesis (called embryogenesis) can tell us a great deal about the function and structure of an adult organism. One of the most important aspects of development to understand is the progression of cell division and differentiation in what will become an adult worm. This is where the DevoWorm project can both address multiple outstanding theoretical issues and provide graphical clarity to the embryogenetic process. As a representative of mosaic development, C. elegans embryogenesis is both tractable in terms of cell number and relatively well-characterized. In this paper, we will lay out a theoretical re-interpretation of embryogenesis in addition to developing an RDF-based computational framework for visualizing the results of this theoretical effort. Our theoretical efforts will ultimately involve the construction of a differentiation tree and data analyses that support the concept of differentiation waves acting to coordinate cellular differentiation and embryonic form. The differentiation tree will also feature a means to perturb development in a manner that mimics phenotypic mutagenesis. This will allow us to understand the selective variability that is inherent in biological development, but that remains so poorly understood. In tandem, these developments will allow us to construct a conceptual and computational framework which can be applied to both mosaic and regulative development.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".