The impact of methanol on behaviour: Dataset from zebrafish (Danio rerio) behavioural research
Bibliographic record
Abstract
In many pharmacological and toxicological studies solvents are used as vehicles for the compound of interest. The solvents themselves may have effects on their own, therefore, it is important to test the impact of the solvent on the preparation prior to conducting the study. Methanol, (CH3OH), is a solvent used in many studies, and one we have used as a vehicle for benzo[a]pyrene. This data contains raw videos of zebrafish after exposure to 0, 0.25%, or 2.5% vol/vol, for 30 minutes prior to behavioral testing. Immediately after exposure, the individual zebrafish were moved to an open field test to quantify movement and location preference and were recorded for 10 minutes. Following the open field trial, a novel object was placed into the center of the arena to examine the exploratory response (boldness) of the fish for a second 10 minute trial. Motion-tracking software (EthoVision XT) was used to quantify the dependent variables (distance moved, time in outer 'thigmotaxis' zone, 'inner' zone, and 'transition' zone). There were no significant differences between groups for any of the variables in either the open field or novel object approach tests. This data suggests that 0.25% and 2.5% methanol does not alter locomotion or location preference in these two tests.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.014 |
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".