Bibliographic record
Abstract
A plant's best strategy for acquiring resources may often depend on the identity of neighbours. Here, I ask whether plants adjust their strategy to local relatedness: individuals may cooperate (reduce competitiveness) with kin but compete relatively intensely with non-kin. In a greenhouse experiment with Ipomoea hederacea, neighbouring siblings from the same inbred line were relatively uniform in height; groups of mixed lines, however, were increasingly variable as their mean height increased. The reproductive yield of mixed and sibling groups was similar overall, but when adjusted to a common mean height and height inequality, the yield of mixed groups was significantly less. Where this difference in yield was most pronounced (among groups that varied most in height), mixed groups tended to allocate more mass to roots than comparable sibling groups, and overall, mixed groups produced significantly fewer seeds per unit mass of roots. These results suggest that, from the group perspective, non-kin may have wasted resources in below-ground competition at the expense of reproduction; kin groups, on the other hand, displayed the relative efficiency that is expected of reduced competitiveness.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".