Embryological origins of developmental stability: Size, shape and fluctuating asymmetry in prenatal random bred mice
Bibliographic record
Abstract
Ontogenetic patterns of fluctuating asymmetry (FA) can be used to test models for the mechanisms underlying stability during embryonic development (developmental stability). In this study, we ask whether developmental processes initially show high levels of instability that are subsequently dampened through active compensatory mechanisms or passive properties of developmental systems or whether the effects of instability accumulate during embryonic development causing random drift away from an earlier stable state. Previous work on this question has dealt with postnatal skeletal growth and thus been unable to effectively distinguish developmental instability from the effects of mechanically mediated variation in bone modeling and remodeling. Here, we report that FA variances of limb skeletal elements in CD1 mice decrease with gestational age from day 14 to birth (day 20.5). Thus, in mouse limbs, skeletal development is characterized by a high level of developmental instability initially that is reduced during subsequent prenatal development. These results are consistent with the existence of active mechanisms that compensate for the effects of minor perturbations or deviations during development. However, they are also consistent with Soule's model of allomeric variation in which the variance of structures is reduced as the number of independent developmental events that produce them increases. This study illustrates that predictions based on morphometric analyses can yield insights into general properties of developmental systems in cases where specific developmental mechanisms are not yet known.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".