Plant and pollinator interactions from British Columbia from Oak Savannah, Shrub-Steppe, and restored hedgerows
Bibliographic record
Abstract
This dataset contains the data analyzed in "Guzman, L.M., Chamberlain, S. and Elle, E. (2021) Network robustness and structure depends on the phenological characteristics of plants and pollinators. Ecology and Evolution" The data comprises plant-pollinator interactions collected in three ecosystems (Oak Savannah, Shrub-Steppe and restored hedgerows) from British Columbia. These three vegetation types comprised three different studies. The average distance between sites within studies was 19km, 18km and 29km for the oak savannah, shrub-steppe and hedgerows respectively. For simplicity we use “pollinator” throughout this paper to refer to insects and hummingbirds observed visiting flowers and contacting reproductive organs, although their effectiveness at transfer of pollen has not been assessed. The networks were comprised largely of bees, with wasps and hoverflies also common. Less common were butterflies and beetles. The plants were largely forbs with some shrubs; insect-pollinated trees were not sampled for largely logistical reasons of tree height but tended to be uncommon in these ecosystems.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".