Raeppli: a whole-tissue labeling tool for live imaging of <i>Drosophila</i> development
Bibliographic record
Abstract
Observation of how cells divide, grow, migrate and form different parts of a developing organism is crucial for understanding developmental programs. Here, we describe a multicolor imaging tool named Raeppli (after the colorful confetti used at the carnival in Basel). Raeppli allows whole-tissue labeling such that the descendants of the majority of cells in a single organ are labeled and can be followed simultaneously relative to one another. We tested the use of Raeppli in the Drosophila melanogaster wing imaginal disc. Induction of Raeppli during larval stages irreversibly labels >90% of the cells with one of four spectrally separable, bright fluorescent proteins with low bias of selection. To understand the global growth characteristics of imaginal discs better, we induced Raeppli at various stages of development, imaged multiple fixed discs at the end of their larval development and estimated the size of their pouch primordium at those developmental stages. We also imaged the same wing disc through the larval cuticle at different stages of its development; the clones marked by Raeppli provide landmarks that can be correlated between multiple time points. Finally, we used Raeppli for continuous live imaging of prepupal eversion of the wing disc.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".