A Standardized Tank Design for the Light Dark Task in Zebrafish
Bibliographic record
Abstract
The light dark paradigm is a common behavioral test used to screen a variety of pharmacological agents, including anxiogenics and anxiolytics. Although most often used in rodents, the light dark task has recently been adapted for use in zebrafish. However, a number of inconsistent findings have been reported for this species. Some have found zebrafish to prefer black, while others report a preference for light. Careful analysis of light dark preference experiments using zebrafish reveals significant variation in testing tank design and test conditions, including lighting and substrate color. Additionally, in some experiments the designated dark side of the testing tank is completely covered, producing a "cave-like" environment which further confounds results. Lastly, authors commonly use the terms "light vs. dark" interchangeably with "white vs. black", when these are two separate factors that may influence preference: illumination level vs. background shade. To address these limitations, we designed testing tanks that differentiate illumination vs. background shade preference in zebrafish. This design allows for simple standardization of light dark testing apparatus in zebrafish, and facilitates more reliable comparison across studies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".