Data from: Divergent brain gene expression profiles between alternative behavioural helper types in a cooperative breeder
Bibliographic record
Abstract
Juveniles of the cooperatively-breeding cichlid fish Neolamprologus pulcher either consistently provide help in form of alloparental egg care ('cleaners') or consistently abstain from helping ('non-cleaners'). These phenotypes are not based on heritable genetic differences. Instead they arise during ontogeny, which should lead to differences in brain structure or physiology, a currently untested prediction. We compared brain gene expression profiles of cleaners and non-cleaners in two experimental conditions, a helping opportunity and a control condition. We aimed to identify (i) expression differences between cleaners and non-cleaners in the control, (ii) changes in gene expression induced by the opportunity, and (iii) differences in plasticity of gene expression between cleaners and non-cleaners. Control cleaners and non-cleaners differed in the expression of a single gene, irx2, which regulates neural differentiation. During the opportunity, cleaners and non-cleaners had three up-regulated genes in common, which were implicated in neuroplasticity, hormonal signalling, and cell proliferation. Thus, the stimulus in the opportunity was sufficiently salient. Cleaners also showed higher expression of seven additional genes that were unique to the opportunity. One of these cleaner-specific genes is implicated in neuropeptide metabolism, indicating that this process is associated with cleaning performance. This suggests that the two types employed different pathways to integrate social information, preparing them for accelerated reaction to future opportunities. Interestingly, three developmental genes were down-regulated between the control and the opportunity in cleaners only. Our results indicate that the two behavioural types responded differently to the helping opportunity, and that only cleaners responded by down-regulating developmental genes.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".