Bibliographic record
Abstract
on F Plant-insect interactions ram slan biol ies, e m sitie and reduced seed production, seedling density and the density of rosette and flowering diffuse knapweed plants. changi y, 2003 and te of nat likely to be successful. With calls for greater emphasis on the effi-cacy of biological control agents (McClay and Balciunas, 2005) it is important to evaluate the impacts of agents that have been re-leased and their characteristics. If the potential for success of par-ticular agents could be predicted in advance, the number of introductions could possibly be reduced, and thus the overall risk associated with adding more foreign species to new environments would also be reduced (Louda et al., 1997, 2003). Since 1970, 12 species of insects have been introduced for bio-logical control (Bourchier et al., 2002) and 10 have become estab-lished. In the early years of the knapweed biological control program considerable effort went into the evaluation of the im-pacts of biological control species in British Columbia, Canada (Roze, 1981; Morrison, 1987; Powell, 1988). These studies showed that agents that merely reduce seed production were not sufficient to reduce plant density. Of the species introduced for the biological control of diffuse knapweed four are now widespread and abundant; two species of Tephritid flies, Urophora affinis Frfld. and Urophora quadrifasciata
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.243 | 0.090 |
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".