Building blocks of a fish head: Developmental and variational modularity in a complex system
Bibliographic record
Abstract
Evolution of the vertebrate skull is developmentally constrained by the interactions among its anatomical systems, such as the dermatocranium and the sensory system. The interaction between the dermal bones and lateral line canals has been debated for decades but their morphological integration has never been tested. An ontogenetic series of 97 juvenile and adult Amia calva (Actinopterygii) was used to describe the patterning and modularity of sensory lateral line canals and their integration with supporting cranial bones. Developmental modules were tested for the otic canal and supratemporal commissure by computing correlations in the branching sequence of groups of pores. Landmarks were digitized on 25 specimens to test a priori hypotheses of variational and developmental modularity at the level of canals and dermal bones. Branching sequence suggests a specific patterning supported by significant positive correlations in the sequence of appearance of branches between bilateral sides. Differences in patterning between the otic canal and the supratemporal commissure and tests of modularity with geometric morphometrics suggest that both canals form distinct modules. The integration between bones and canals was insufficient to detect a module. However, both components were not independent. Groups of pores tended to disappear without affecting other groups of pores suggesting that they are quasi-independent units acting as modules. This study provides evidence of a hierarchical organization for the modular sensory system that could explain variation of pattern of canals among species and their association with dermal bones.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".