Neural network detected in a presumed vestigial trait: ultrastructure of the salmonid adipose fin
Bibliographic record
Abstract
A wide variety of rudimentary and apparently non-functional traits have persisted over extended evolutionary time. Recent evidence has shown that some of these traits may be maintained as a result of developmental constraints or neutral energetic cost, but for others their true function was not recognized. The adipose fin is small, fleshy, non-rayed and located between the dorsal and caudal fins on eight orders of basal teleosts and has traditionally been regarded as vestigial without clear function. We describe here the ultrastructure of the adipose fin and for the first time, to our knowledge, present evidence of extensive nervous tissue, as well as an unusual subdermal complex of interconnected astrocyte-like cells equipped with primary cilia. The fin contains neither adipose tissue nor fin rays. Many fusiform actinotrichia, comprising dense striated macrofibrils, support the free edge and connect with collagen cables that link the two sides. These results are consistent with a recent hypothesis that the adipose fin may act as a precaudal flow sensor, where its removal can be detrimental to swimming efficiency in turbulent water. Our findings provide insight to the broader themes of function versus constraints in evolutionary biology and may have significance for fisheries science, as the adipose fin is routinely removed from millions of salmonids each year.
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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 | 0.000 | 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) | 0.001 | 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".