Data from: Testing potential selective agents acting on leaf shape in Ipomoea hederacea: predictions based on an adaptive leaf shape cline
Bibliographic record
Abstract
Leaf shape is a highly variable phenotype, and is likely influenced by many sources of selection. Ipomoea hederacea exhibits an adaptive latitudinal cline in leaf shape, which is controlled by a single Mendelian locus: lobed individuals dominate the north with entire-shaped individuals mostly in the south. We test if the following candidate selective agents, suggested by the literature, are responsible for the cline: differential insect herbivory, genetic correlations with other clinal traits like flowering time and growth rate, and thermoregulatory differences. We planted 1680 F3 individuals, segregating for leaf shape, in the north of I. hederacea's range, where we expected lobed genotypes to have higher fitness. Individuals were assigned to insect removal or control treatments, and we scored herbivory, flowering time, growth rate, leaf temperature, and fitness (seed number). Herbivory, flowering, and growth rate had significant fitness effects, but none differed between leaf shapes. Lobed leaves were consistently warmer at night, but no performance advantage was detected. Finally, we detected no overall fitness differences between leaf shape genotypes, whether we controlled for other traits under selection or not. Our data suggest these candidate selective agents may not be important contributors to the cline, and alternative approaches to understanding the mechanisms maintaining the leaf shape cline in I. hederacea may be necessary.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".