The effects of commonly used anaesthetics on colour measurements across body regions in the poeciliid fish, <i>Girardinus metallicus</i>
Bibliographic record
Abstract
The effects of common anaesthetics on the hue, saturation and brightness measurements of the poeciliid fish Girardinus metallicus were investigated in two experiments. For both experiments the coloration of four body regions was measured from digital images of the same males obtained under three conditions: (1) control (in a water-filled chamber); (2) anaesthetised with MS-222; and (3) anaesthetised with eugenol (clove oil). In experiment 1 anaesthetised fish were photographed out of water. In experiment 2 all photographs were taken in a water-filled chamber. Anaesthetics altered coloration in both experiments. In the more methodologically consistent experiment 2 we found significantly different hue, increased saturation and decreased brightness in anaesthetic v. control conditions, consistent with darkening caused by the anaesthetics. The body regions differed in coloration consistent with countershading but did not differentially change in response to anaesthesia. These findings suggest that photographing fish in a water-filled chamber without anaesthetic is preferable for obtaining digital images for colour analysis and that multiple body regions of fish should be measured when assessing coloration patterns meaningful in behavioural contexts, to account for the gradients caused by countershading. We are encouraged that some researchers employ such methods already and caution against using anaesthetics except when absolutely necessary for immobilisation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".