Thermal activation of escape swimming in post-hatching <i>Xenopus laevis</i> frog larvae
Bibliographic record
Abstract
Survival requires the selection of appropriate behavioural responses in the face of danger. With respect to the threat of predation, both the decision to escape and the underlying neuronal mechanisms have been extensively studied, but processes that trigger evasion of abiotic stressors, which are potentially hazardous to survival, are less well understood. Here, we document the interplay between rhythmic locomotory and 'C-start' escape swimming in Xenopus frog larvae when exposed to hyperthermic conditions. As temperature rises, swim cycle frequency increases while swim bout duration decreases, until swimming can no longer be initiated by sensory stimuli. Above a critical higher temperature, more intense sequences of spontaneous high amplitude C-start escape activity occur. Each C-start is followed by a few cycles of fast rhythmic swimming in which activity alternates between the two sides. The initial, high amplitude ventral root burst of an escape sequence propagates rostrocaudally approximately threefold faster than subsequent cycles. The high conduction velocity of this initial burst is consistent with the activation of a Mauthner neuron, one of a pair of giant reticulospinal neurons in fish and amphibians. In support of the involvement of a Mauthner neuron, unilateral lesions of the caudal hindbrain eliminated escape activity on the operated side, but activity remained on the un-operated side. Behaviourally, tadpoles responded to temperature ramps with a sequence of C-start responses in which the body arced through approximately 130 degrees in 22 ms, followed by high frequency swimming. These results suggest that high temperature activates the Mauthner neurons to trigger C-start escape behaviour.
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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".