Surface landmark quantification of embryonic mouse craniofacial morphogenesis
Bibliographic record
Abstract
BACKGROUND: Morphometric quantification of subtle craniofacial variation in studies of experimentally modified embryonic mice has proved valuable in determining the effects of developmental perturbations on craniofacial morphogenesis. The direct comparison of landmark coordinate data from embryos of many different mouse strains and mouse models can advance our understanding of the bases for craniofacial variation. We propose a standard set of craniofacial surface landmarks, for use with embryonic day (E) 10.5-12.5 mice, to serve as the foundation for this type of data compilation and analysis. We quantify the intra- and inter-observer landmark placement variation associated with each landmark and determine how the results of a simple ontogenetic analysis might be influenced by selection of landmark set. RESULTS: Intraobserver landmark placement error for experienced landmarkers generally remains below 0.1 mm, with some landmarks exhibiting higher values at E11.5 and E12.5. Interobserver error tends to increase with embryonic age and those landmarks defined on wide inflections of curves or facial processes exhibit the highest error. Landmarks with highest intra- or inter-observer are identified and we determine that their removal from the dataset does not significantly change the vectors of craniofacial shape change associated with an ontogenetic regression. CONCLUSIONS: Our quantification of landmark placement error demonstrates that it is preferable for a single observer to identify all landmark coordinates within a single study and that significant training and experience are necessary before a landmarker can produce data for use in larger meta-analyses. However, we are confident that this standard landmark set, once landmarks with higher error are removed, can serve as a foundation for a comparative dataset of facial morphogenesis across various mouse populations to help identify the developmental bases for phenotypic variation in the craniofacial complex.
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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 | 0.001 | 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".