Data from: A phylogenetic analysis of trait convergence in the spring flora
Bibliographic record
Abstract
In temperate deciduous forests, spring flowering plants exhibit remarkable similarity in a number of characteristics, including reproductive, vegetative, and ecological traits. The apparent convergence of floral traits, especially corolla colour, among spring flowering species has been well documented, but remains poorly understood. Here we review adaptive hypotheses and predictions that have been proposed to explain the apparent correlation between spring flowering and a suite of traits. We investigated the correlation between flowering phenology (i.e., spring or nonspring) and several key traits using phylogenetic comparative methods. Through this analysis we were able to confirm the existence of a correlation for five of the six traits examined. Specifically, spring flowering is shown to have evolved in a correlated fashion with reproductive schedule (perennial vs. annual), light corolla colour, fruit type, growth form, and forest strata layer. In general, our survey determined that spring flowering species are perennial, have light coloured corollas, a herbaceous growth form, and tend to occupy the understory of the forest. These results are discussed in light of the reviewed adaptive hypotheses and the spring pollination environment.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".