Plating larval zebrafish prior to the day of experimentation has no impact on spontaneous swimming and startle responses
Bibliographic record
Abstract
Behavioural testing in larval zebrafish often involves pipetting the larvae into well plates for individual testing. Transferring larvae into plates the day prior to experimentation can increase efficiency of testing. Furthermore, pharmacological and toxicological studies can require a prolonged dosing period requiring the larvae to be pre-plated into the well plate the day prior to experimentation. Here, we compared the behavioural impact of pre-plating larval zebrafish at 4 days post-fertilization (dpf) to fish transferred at 5 dpf on the day of testing. Motion-tracking software was used to examine locomotion and zone preference, and responses to light, dark, and mechanical startle stimuli. We found no significant differences in distance moved, time spent in the thigmotaxis zone (outside edge of the arena), high mobility, immobility, light startle, dark startle, and mechanical startle responses. This data suggests that pre-plating larval zebrafish one day prior to testing does not have a significant impact on behaviour in a spontaneous swim task, dark startle test, light startle test, or mechanical startle test. Pre-plating larval zebrafish can increase the efficiency of behavioural testing.•Compare plating larvae one day prior to testing to plating day of testing.•Test the behaviour in a spontaneous swimming test, and measure light-, dark-, and mechanical-startle responses.•There were no significant differences in locomotion or startle responses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".