Data from: Same trait, different genes: pelvic spine loss in three brook stickleback populations in Alberta
Bibliographic record
Abstract
The genetic basis of phenotypic or adaptive parallelism can reveal much about constraints on evolution. This study investigated the genetic basis of a canonically parallel trait: pelvic spine reduction in sticklebacks. Pelvic reduction has a highly parallel genetic basis in threespine stickleback in populations around the world, always involving a deletion of the pel1 enhancer of Pitx1. In three populations of brook stickleback in Alberta, Canada, pelvic reduction did not involve Pitx1. Instead, pelvic reduction in one population involved a mutation in an exon of Tbx4, and it involved a mutation in an intron of Lmbr1 in the other two populations. Hence, the parallel phenotypic evolution of pelvic spine reduction across stickleback genera, and among brook stickleback populations, has a non-parallel genetic basis. This suggests that there is redundancy in the genetic basis of this adaptive polymorphism, but it is not clear whether this indicates a lack of constraint on the evolution of this adaptive trait. Whether the different pleiotropic effects of different mutations have different fitness consequences, or whether certain pelvic reduction mutations confer specific benefits in certain environments, remains to be determined.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.010 |
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".