4D atlas of the mouse embryo for precise morphological staging
Bibliographic record
Abstract
After more than a century of research, the mouse remains the gold-standard model system, for it recapitulates human development and disease and is quickly and highly tractable to genetic manipulations. Fundamental to the power and success of using a mouse model is the ability to stage embryonic mouse development accurately. Past staging systems were limited by the technologies of the day, such that only surface features, visible with a light microscope, could be recognized and used to define stages. With the advent of high-throughput 3D imaging tools that capture embryo morphology in microscopic detail, we now present the first 4D atlas staging system for mouse embryonic development using optical projection tomography and image registration methods. By tracking 3D trajectories of every anatomical point in the mouse embryo from E11.5 to E14.0, we established the first 4D atlas compiled from ex vivo 3D mouse embryo reference images. The resulting 4D atlas comprises 51 interpolated 3D images in this gestational range, resulting in a temporal resolution of 72 min. From this 4D atlas, any mouse embryo image can be subsequently compared and staged at the global, voxel and/or structural level. Assigning an embryonic stage to each point in anatomy allows for unprecedented quantitative analysis of developmental asynchrony among different anatomical structures in the same mouse embryo. This comprehensive developmental data set offers developmental biologists a new, powerful staging system that can identify and compare differences in developmental timing in wild-type embryos and shows promise for localizing deviations in mutant 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".