Replication alert: behavioural lateralisation in a detour test is not repeatable in fishes
Bibliographic record
Abstract
Behavioural lateralisation, defined as the asymmetric expression of cognitive functions, is reported to enhance key fitness-relevant traits such as predator escape performance, multitasking abilities, and group coordination. Therefore, studies reporting negative effects on lateralisation in fish due to environmental stressors such as ocean acidification, hypoxia, and pollutants are worrisome. However, such studies have focussed on population-level measures, without validating whether lateralisation is consistent within individuals across time. We conducted a multi-species, international assessment of the repeatability (R) of lateralisation in four previously studied fish species using the common detour test, and re-analysed a published dataset (on guppies) using new statistical methods. We expected the three shoaling species to exhibit greater within-individual consistency in lateralisation than their non-shoaling counterparts given previous reports of stronger lateralisation in group-living fishes. However, both absolute and relative lateralisation scores were highly non-repeatable in all five species (0.01
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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 | 0.014 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".