Mouse embryonic phenotyping by morphometric analysis of MR images
Bibliographic record
Abstract
A new method is described for automatic detection of subtle morphological phenotypes in mouse embryos. Based on high-resolution magnetic resonance imaging scanning and nonlinear image alignment, this method is demonstrated by comparing the morphology of two inbred strains, C57BL/6J and 129Sv/S1ImJ, at 15.5 days postconception. Mouse embryo morphology was found to be highly amenable to this kind of analysis with very low levels (on average 110 μm) of residual anatomical variation within strains after linear differences in pose and scale are removed. Mapping of local size differences showed that C57BL/6J embryos were larger than 129Sv/S1ImJ embryos, although these differences were not uniformly distributed across the anatomy. Expressed in terms of organ volumes, heart and lung were larger in C57BL/6J embryos, while brain and liver were comparable in volume between strains. The positive relationship between organ size and embryo size was consistent for the two strains but differed by organ, with the brain and liver being the least variable. Together these findings suggest the power of this technique for detecting subtle phenotypic differences arising from mutated genes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".