Use of axonal projection patterns for the homologisation of cerebral nerves in Opisthobranchia, Mollusca and Gastropoda
Bibliographic record
Abstract
INTRODUCTION: Gastropoda are guided by several sensory organs in the head region, referred to as cephalic sensory organs (CSOs). These CSOs are innervated by distinct nerves. This study proposes a unified terminology for the cerebral nerves and the categories of CSOs and then investigates the neuroanatomy and cellular innervation patterns of these cerebral nerves, in order to homologise them. The homologisation of the cerebral nerves in conjunction with other data, e.g. ontogenetic development or functional morphology, may then provide insights into the homology of the CSOs themselves. RESULTS: Nickel-lysine axonal tracing ("backfilling") was used to stain the somata projecting into specific nerves in representatives of opisthobranch Gastropoda. Tracing patterns revealed the occurrence, size and relative position of somata and their axons and enabled these somata to be mapped to specific cell clusters. Assignment of cells to clusters followed a conservative approach based primarily on relative location of the cells. Each of the four investigated cerebral nerves could be uniquely identified due to a characteristic set of soma clusters projecting into the respective nerves via their axonal pathways. CONCLUSIONS: As the described tracing patterns are highly conserved morphological characters, they can be used to homologise nerves within the investigated group of gastropods. The combination of adequate number of replicates and a comparative approach allows us to provide preliminary hypotheses on homologies for the cerebral nerves. Based on the hypotheses regarding cerebral nerve homology together with further data on ultrastructure and immunohistochemistry of CSOs published elsewhere, we can propose preliminary hypotheses regarding homology for the CSOs of the Opisthobranchia themselves.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".