Conservation of gene function in behaviour
Bibliographic record
Abstract
Behaviour genetic research has shown that a given gene or gene pathway can influence categorically similar behaviours in different species. Questions about the conservation of gene function in behaviour are increasingly tractable. This is owing to the surge of DNA and 'omics data, bioinformatic tools, as well as advances in technologies for behavioural phenotyping. Here, we discuss how gene function, as a hierarchical biological phenomenon, can be used to examine behavioural homology across species. The question can be addressed independently using different levels of investigation including the DNA sequence, the gene's position in a genetic pathway, spatial-temporal tissue expression and neural circuitry. Selected examples from the literature are used to illustrate this point. We will also discuss how qualitative and quantitative comparisons of the behavioural phenotype, its function and the importance of environmental and social context should be used in cross-species comparisons. We conclude that (i) there are homologous behaviours, (ii) they are hard to define and (iii) neurogenetics and genomics investigations should help in this endeavour.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".