Editorial: Zebrafish Cognition and Behavior
Bibliographic record
Abstract
Understanding animal cognition has been of interest to scientists for well over a century (e.g., Melrose, 1921). Cognition is broadly defined as the neural and behavioral processes associated with the acquisition, retention, and use of information (Dukas, 2004). Since the discovery of multiple memory systems and of the fundamental role of the hippocampus in relational learning and memory in humans (Penfield and Milner, 1958), one exciting focus of study has been to determine how animals encode, transform, compute and manipulate spatial, temporal, and contextual information from their environment, and how this information is utilized to organize behavioral responses (Cook, 1993). Initial studies used simple visual and acoustic stimuli, such as colored lights and distinct sounds. However, the use of such stimuli hindered the study of animal cognition because it did not allow the subjects to fully engage their full information processing capabilities. To address this issue, researchers started using more complex stimuli, such as objects, photos, and videos. These studies demonstrated a higher level of cognitive processing not previously attributed to animals (Dukas, 2004). As the field of learning and memory advanced, studies started to show remarkable similarities between the cognitive processes of animals and humans. Animals have been found to be even able to learn varied and sophisticated concepts, exhibit mental processes, such as symbol coding and organization, to form spatial, temporal, and numerical abstractions and perceive cause and effect relationships (Wynne, 2001).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".