GloPL, a global data base on pollen limitation of plant reproduction
Bibliographic record
Abstract
Plant reproduction relies on transfer of pollen from anthers to stigmas, and the majority of flowering plants depend on biotic or abiotic agents for this transfer. A key metric for characterizing if pollen receipt is insufficient for reproduction is pollen limitation, which is assessed by pollen supplementation experiments. In a pollen supplementation experiment, fruit or seed production by flowers exposed to natural pollination is compared to that following hand pollination either by pollen supplementation (i.e. manual outcross pollen addition without bagging) or manual outcrossing of bagged flowers, which excludes natural pollination. The GloPL database brings together data from 2969 unique pollen supplementation experiments reported in 927 publications published from 1981 to 2015, allowing assessment of the strength and variability of pollen limitation in 1265 wild plant species across all biomes and geographic regions globally. The GloPL database will be updated and curated with the aim of enabling the continued study of pollen limitation in natural ecosystems and highlighting significant gaps in our understanding of pollen limitation.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.031 | 0.028 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".