Phenotyping stimulus evoked responses in larval zebrafish
Bibliographic record
Abstract
The aim of the present study was to establish an effective method of analyzing individual variation in stimuli-evoked behavioural responses. The same genetic, environmental and experimental conditions were maintained throughout in order to limit variation. Naive larval zebrafish ages 5 and 7 days post fertilization were exposed to a water or chemical stimulus (adenosine) and observed for changes in bursting activity. Fish exposed to water demonstrated highly variable responses including increases, decreases and biphasic changes in bursting activity. Since the experimental settings were controlled, these differences between individuals may be related to fish personality. To interpret our data we applied a novel threshold based sorting protocol to each fish. Individuals were successfully grouped into 24 pre-defined behavioural response phenotypes. The phenotypes had distinct movement patterns and contained different proportions of fish. The same sorting method applied to adenosine exposed fish resulted in similar ratios of phenotypes. This suggests that solution addition as a stimulus evokes different yet replicable responses in a fish population. Comparisons within phenotypes and across treatments revealed subtle differences in activity between water and adenosine exposed fish. Adenosine treated fish had either increased or decreased bursting frequency depending on the response type. These results suggest that phenotypic separation prior to analysis enables observation of treatment differences that may have otherwise been missed. In summary, the present study demonstrates the practice of behavioural phenotyping as a successful method for analysis of individual variation in a population.
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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".