Ignored patterns in studies of local adaptations: When the grass is greener on the allopatric site
Bibliographic record
Abstract
Recently, the focus within microevolutionary studies has been on the ecological divergence of populations. One subset of this research field includes studies on local adaptation. This approach is useful for studying whether or not adaptive spatial variation takes place in a metapopulation context. There is growing body of research studying local adaptations of populations, and much of this has used a formal test for assessing the existence of local adaptation. According to Kawecki and Ebert (2004), the “Local vs. foreign” criterion is fulfilled if the local population has higher fitness than other populations in its own locality and “Home vs. away” is fulfilled if a population has higher fitness in the sympatric than allopatric environment. Interestingly, interpretation of results not fulfilling these criteria has received scant attention even though the question of how to measure local adaptation is vital for the study field. At present, there is an extensive volume of published results showing other kinds of patterns than those proposed by the “Local vs. foreign” or “Home vs. away” criteria. Here, we highlight one of these alternative patterns that we believe may have an adaptive background and may show local adaptation not recognized by the above-mentioned criteria.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".