Bibliographic record
Abstract
Like other hydrozoan medusae, Aglantha lacks a brain, but the two marginal nerve rings function together as a central nervous system. Twelve neuronal and two excitable epithelial conduction systems are described and their interactions summarized. Aglantha differs from most medusae in having giant axons. It can swim and contract its tentacles in two distinct ways (escape and slow). Escape responses are mediated primarily by giant axons but conventional interneurons are also involved in transmission of information within the nerve rings during one form of escape behavior. Surprisingly, giant axons provide the motor pathway to the swim muscles in both escape and slow swimming. This is possible because these axons can conduct calcium spikes as well as sodium spikes and do so on an either/or basis without overlap. The synaptic and ionic bases for these responses are reviewed. During feeding, the manubrium performs highly accurate flexions to points at the margin. At the same time, the oral lips flare open. The directional flexions are conducted by FMRFamide immunoreactive nerves, the lip flaring by an excitable epithelium lining the radial canals. Inhibition of swimming during feeding is due to impulses propagated centrifugally in the same epithelium. Aglantha probably evolved from an ancestor possessing a relatively simple wiring plan, as seen in other hydromedusae. Acquisition of giant axons resulted in considerable modification of this basic plan, and required novel solutions to the problems of integrating escape with non-escape circuitry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".